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Abstract

Objective

This study explored the relationship between perceptions of health mis/disinformation on social media and belief that progress has been made in curing cancer.

Methods

We analyzed cross-sectional, retrospective data collected from 4246 adult social media users in the 2022 Health Information National Trends Survey (HINTS 6). The outcome variable was the belief in whether progress has been made in curing cancer. The primary predictor variable was the perception of health mis/disinformation on social media, categorized as ‘Substantial’ and ‘< Substantial’. We also examined whether the relationship varied by health care system trust, frequency of social media use, and education. The analysis controlled for demographic, socioeconomic, and health-related factors.

Results

Perception of substantial social media health mis- and disinformation was associated with a lower likelihood of believing progress has been made in curing cancer (odds ratios = 0.74, 95% CI = 0.59-0.94). Persons who perceived substantial social media health mis-and disinformation and had low trust in the health care system were less likely to believe progress has been made in curing cancer: 36% (95% CI: 28-45%). Persons who perceived substantial social media health mis-and disinformation and used social media less than daily were less likely to believe progress has been made in curing cancer: 44% (95% CI: 36-52%). Persons without a college degree who perceived substantial social media health mis-and disinformation were less likely to agree that progress has been made in curing cancer: 44% (95% CI: 39-50%).

Conclusion

Exposure to misinformation on social media may be associated with negative attitudes about advances in curing cancer, particularly among social media users with low trust in the health care system trust, less frequent social media users, or those without a college degree.

Keywords

United States cross-sectional study trust consumer health information misinformation disinformation education attitude to health social media

Introduction

Social media has revolutionized the field of health communication, acting as a channel for both reliable and deceptive health-related information.¹ Social media platforms serve as a crucial source of health information for many individuals and play a vital role in public health communication.^2-4 Nevertheless, the unrestricted and unregulated nature of these platforms has also enabled the widespread dissemination of health misinformation and disinformation.^5,6 Misinformation refers to false or misleading information shared unintentionally, while disinformation denotes the deliberate creation and dissemination of false information.⁷ The consequences of such misinformation and disinformation are far-reaching, potentially leading to harmful health behaviors, decreased vaccination rates, and the undermining of public trust in health institutions.^8,9

The dynamics of information seeking and belief formation can be explored through the lens of the Health Belief Model (HBM).¹⁰ The HBM posits that individuals’ perceptions of susceptibility to cancer and the severity of the disease can influence their motivation to seek information. In this context, we can examine if exposure to perceived health misinformation on social media shapes individual perceptions of cancer curability, potentially lowering their perceived susceptibility or severity.¹¹ This could then indirectly influence their belief in advancements made in cancer treatment.

Cancer is a critical area of focus because it remains one of the leading causes of death worldwide.¹² Beliefs about progress in curing cancer can significantly impact public support for research funding, participation in clinical trials, and adherence to preventive measures and treatments.^13-15 Examining these beliefs in the context of misinformation and disinformation is essential because skewed perceptions can hinder efforts to improve cancer outcomes.

Beliefs about cancer can be shaped by education, as suggested by the HBM.¹⁰ Individuals with higher educational attainment might be better equipped to critically evaluate information, potentially leading to a lower perception of susceptibility to misinformation and a more nuanced understanding of the disease’s severity.¹⁶ Recent research supports this notion, suggesting that education enhances critical thinking skills and source verification when evaluating online health information.^17,18

Additionally, trust in the health care system can act as a filter for information credibility.¹⁹ In this study, “trust in the health care system” is defined as the confidence individuals have in the competence, reliability, and integrity of health care providers and institutions.²⁰ People with high trust are more likely to view information from established medical sources as credible, while low trust can make individuals more susceptible to misinformation.^21,22 Studies have shown a link between trust in health care providers and adherence to treatment plans, highlighting the influence of trust on how individuals interpret and act upon health information.^23-26 By incorporating the moderating effects of both education and trust, this study can offer a richer understanding of how misinformation disrupts the information-seeking process and shapes health beliefs.²⁷

Our research explores the interplay between the perception of health misinformation and disinformation on social media and the belief in the progress made in curing cancer. The guiding research questions are: What is the relationship between perceptions of health misinformation and disinformation on social media and the belief in advancements in cancer treatment? And how does this relationship vary by trust in the health care system, frequency of social media use, and educational attainment? Understanding these dynamics is vital for devising public health strategies and communication campaigns to counter misinformation and enhance public awareness of medical progress. By pinpointing the factors influencing beliefs about medical advancements, findings from this study can help inform tailored interventions to enhance public perceptions and foster trust in health care innovations.

The research questions drive several hypotheses. The first hypothesis posits that individuals perceiving substantial health misinformation and disinformation on social media are less likely to believe in significant progress in curing cancer. This is premised on the idea that misinformation and disinformation can skew public perceptions of scientific progress and erode trust in medical advancements. While it is conceptually possible that trust in medical advancements might influence perceptions of misinformation, this study focuses on the more direct pathway where misinformation impacts trust. The second hypothesis suggests that those with low trust in the health care system, compounded by negative perceptions, are least likely to acknowledge progress in cancer treatment. This recognizes that trust in the health care system is instrumental in shaping health beliefs and attitudes, and that misinformation and disinformation can further undermine this trust. The third hypothesis suggests that the frequency of social media use will moderate the relationship between perceived health misinformation and beliefs about cancer progress. Specifically, less frequent social media users that perceive substantial misinformation are hypothesized to be more vulnerable to its negative effects, making them significantly less likely to believe in progress in curing cancer compared to persons that do not perceive substantial misinformation. This hypothesis highlights the potential compounding effect of both misinformation and lower frequency of engagement with social media on public health perceptions.¹¹ The fourth hypothesis proposes that individuals with lower educational attainment, particularly those without a college degree, are less likely to believe in advancements when they perceive high levels of misinformation and disinformation. This acknowledges the role of education in fostering critical thinking skills necessary to distinguish credible information from misinformation and disinformation.

Methods

Data

This retrospective, cross-sectional study utilized nationally representative data from the Health Information National Trends Survey 6 (HINTS 6). HINTS 6 surveys non-institutionalized adults (18 years and older) in the United States (US) about health communication and cancer prevention attitudes and behaviors. The data were collected via mail and online surveys from March to November 2022, achieving a response rate of 28.1%. Detailed survey methodology is available from the National Cancer Institute.²⁸ Participants who reported not using social media in the survey item that asked about perceptions of social media information were excluded (N = 1211). In addition, we used listwise deletion for missing information on any of the variables used in the study (N = 713), resulting in a final, nationally representative sample of 4246 adult social media users. We conducted post-hoc power calculations to ensure the adequacy of our sample size. Given the effect sizes observed in the analysis, our sample size of 4246 respondents provided over 80% power to detect significant associations at a 0.05 significance level, particularly for the primary predictor variable (perception of health mis/disinformation on social media).

Measures

The outcome measure was derived from respondents’ answers to the question, “How much progress has been made in curing cancer?” This measure has been used to investigate cancer fear, worry, and perceived risk.^26,29-31 Response options included: “almost none,” “a little,” “don’t know,” “some,” and “a lot.” Following a recent study, this measure was dichotomized into “progress” (“some” or “a lot”) vs “no progress” (“almost none,” “a little,” or “don’t know”).²⁶

The primary predictor variable assessed perceptions of health misinformation and disinformation on social media with the question, “How much of the health information that you see on social media do you think is false or misleading?” Responses were dichotomized as “substantial” (“a lot”) versus “less than substantial” (“none,” “a little,” or “some”), consistent with past studies.^7,22,25

We tested mechanisms based on the theoretical framework: trust in the health care system, social media use, and education level. Trust in the health care system was measured by asking, “How much do you trust the health care system (for example, hospitals, pharmacies, and other organizations involved in health care)?” Responses were dichotomized as high (“very” and “somewhat”) vs low (“not at all” and “a little”), based on prior literature.^32,33 Social media use was categorized as daily vs less than daily (including “never,” “weekly,” “monthly”). Education level was categorized as not having a college degree vs having a college degree or higher.

Control variables included demographic characteristics, health-related factors, and social media utilization. Demographic variables included age (18-49, 50-64, or 65+), sex (male or female), marital status (married/cohabiting, formerly married, or never married), self-reported race and ethnicity (non-Latino White, non-Latino Black, non-Latino Other, or Latino), education level (college degree or higher vs less than a college degree), residence (metropolitan or nonmetropolitan), full-time employment status, and household income perceptions (very/difficult on present income, getting by on present income, and living comfortably on present income). Health-related factors included health insurance status (insured or uninsured), unmet need for medical care (defined as delaying or not receiving medically necessary care), self-rated overall health status (excellent/very good/good or fair/poor), and personal and family history of cancer.

Statistical Analysis

Descriptive statistics were calculated as survey-weighted percentages. Bivariable relationships between the outcome and predictor variables were assessed using cell percentages and design-based Pearson Chi-Square tests. Multivariable logistic regression was conducted to examine the main effect of perceptions of misinformation/disinformation on beliefs about progress in curing cancer. Sensitivity analyses using ordered logit regression assessed whether results varied when using the ordinal version of the outcome variable.

Interaction effects between the primary predictor and secondary predictor variables were calculated to estimate the theorized pathways linking social media misinformation/disinformation, education level, health care system trust, frequency of social media use, and beliefs about cancer treatment progress. Predicted probabilities were derived from interaction results using the margins command in Stata for ease of interpretation. All analyses were conducted with StataNow/MP 18.5 and accounted for survey weights and design using jackknife replicate weights for variance estimation. Statistical significance was set at an alpha level of 0.05. We followed the STROBE guidelines for cross-sectional studies.³⁴

Ethical Considerations

These publicly available, de-identified data did not require institutional review board approval, as determined by the University of Texas Southwestern Medical Center human research protection program.

Results

Table 1 presents demographic characteristics and their correlations with perceptions of progress in cancer treatment among 4246 respondents. Overall, 54% believe that significant advancements have been made in the treatment of cancer, while 46% think otherwise. Respondents encountering lower amounts of false health information on social media are more likely to believe in progress, with 36% holding this view, compared to 18% among those exposed to a significant amount of false information. Daily social media users also exhibit higher confidence in progress (37%) than those who use it less frequently (17%).

Table 1.

Sample Size and Survey Weighted Percentages, HINTS 6, 2022, N = 4246.

	Overall		Progress Made in Curing Cancer
	N	%	No progress, %	Progress, %	P-value
How much progress has been made in curing cancer?
No progress	1885	46
Progress	2361	54
Perception of social media health mis-disinformation
< substantial	2723	64	28	36	0.05
Substantial	1523	36	18	18
Frequency of social media Visits
< daily	1443	31	14	17	0.74
Daily	2803	69	32	37
Age
18-49	1802	58	29	29	<0.001
50-64	1254	27	12	15
65+	1190	15	5	10
Gender
Male	1617	48	23	25	0.26
Female	2629	52	23	29
Marital status
Married/cohabiting	2334	57	24	33	0.07
Formerly married	1043	10	5	5
Never married	869	33	16	17
Rural/urban designation
Nonmetro	531	12	6	6	0.31
Metro	3715	88	40	48
Race/ethnicity
Non-latino white	2430	61	24	37	<0.001
Non-latino black	658	11	6	5
Latino	772	17	10	7
Non-latino other	386	11	6	5
Education
Not college graduate	2087	64	32	32	<0.001
College graduate or higher	2159	36	14	22
Full time employment
No	1953	41	17	24	0.01
Yes	2293	59	29	30
Feelings about household income
Finding it very/difficult on present income	831	19	12	7	<0.001
Getting by on present income	1559	37	17	20
Living comfortably on present income	1856	44	17	27
Health insurance
Uninsured	366	11	6	5	0.03
Insured	3880	89	40	49
Unmet need for medical care
No	2853	68	30	38	0.01
Yes	1373	32	16	16
General health
Good/fair/poor	690	15	8	7	0.03
Excellent/Very good	3556	85	38	47
Personal history of cancer
No	3686	91	43	48	<0.001
Yes	560	9	3	6
Family history of cancer
No or not sure	1291	35	17	18	0.26
Yes	2955	65	29	36
Trust of health care system
High	3593	83	35	48	<0.001
Low	653	17	11	6

*P-value calculated with design-based Pearson Chi-Square test.

Socially disadvantaged populations are less likely to report perceptions of progress in cancer treatment than socially advantaged populations. Younger respondents (aged 18-49) demonstrate a stronger belief in progress, with 29% expressing this view, in contrast to 15% of those aged 50-64 and 10% of those aged 65 and above. Both males and females show similar perceptions, with 25% of males and 29% of females believing in progress. Married or cohabiting individuals are more likely to believe in progress (33%) compared to formerly married individuals (5%) and those never married (17%). There is a notable difference in belief in progress between respondents in metropolitan (48%) and nonmetropolitan areas (6%). Non-Latino Whites are more inclined to believe in progress (37%) compared to Non-Latino Blacks (5%), Latinos (7%), and Non-Latino Others (5%). Educational attainment influences perceptions, with 32% of individuals without a college degree believing in progress, compared to 22% of those with a college degree or higher. Full-time employment correlates with a higher belief in progress (30%) compared to those not employed full-time (24%). Financial stability also plays a role, with 27% of those living comfortably believing in progress, vs 7% of those struggling financially.

Insurance status significantly impacts belief in progress, with 49% of insured individuals holding this view, compared to 5% of uninsured individuals. Those without unmet medical needs are more likely to believe in progress (38%) compared to those with unmet needs (16%). Good physical health correlates strongly with belief in progress, with 47% of those in excellent or very good health endorsing this view, compared to 7% of those in fair or poor health. Personal and family history of cancer also influenced perceptions. Individuals without a personal history of cancer are more likely to believe in progress (48%) compared to those with a history of cancer (6%). Those with a family history of cancer are more inclined to believe in advancements (36%) compared to those without or unsure of their family history (18%). Trust in the health care system is a significant factor, with 48% of those with high trust in the system believing in progress, compared to 6% of those with low trust.

Table 2 presents the results of a multivariable logistic regression analysis exploring the relationship between perceptions of mis/disinformation on social media and the belief that progress has been made in curing cancer. The odds of believing in progress in curing cancer for individuals perceiving substantial health mis/disinformation on social media were significantly lower than for those perceiving less mis/disinformation (OR = 0.74, 95% CI = 0.59-0.94). Significant associations were also observed with age, race/ethnicity, education, full-time employment, feelings about household income, personal history of cancer, and trust in the health care system. Specifically, older adults (65+) had 40% higher odds of the outcome compared to younger adults (18-49). Non-Latino Black and Latino individuals have 44% and 43% lower odds of the outcome, respectively, compared to Non-Latino White individuals. College graduates have 47% higher odds of the outcome compared to non-college graduates. Full-time employed individuals have 29% lower odds of the outcome compared to those not employed full time. Individuals getting by or living comfortably on their present income have 53% and 60% higher odds of the outcome, respectively, compared to those finding it very/difficult. Individuals with a personal history of cancer have 50% higher odds of the outcome. Individuals with low trust in the health care system have 52% lower odds of the outcome.

Table 2.

Multivariable Logistic Regression, HINTS 6, 2022, N = 4246.

	Odds Ratio	Lower 95% CI	Upper 95% CI	P-value
Perception of social media health mis-disinformation
< substantial
Substantial	0.74	0.59	0.94	0.01
Age
18-49
50-64	1.08	0.83	1.40	0.57
65+	1.40	1.01	1.95	0.05
Gender
Male
Female	1.08	0.89	1.32	0.43
Marital status
Married/cohabiting
Formerly married	0.72	0.54	0.95	0.02
Never married	1.06	0.82	1.37	0.64
Rural/urban designation
Nonmetro
Metro	1.20	0.90	1.59	0.21
Race/ethnicity
Non-latino white
Non-latino black	0.56	0.39	0.82	0.00
Latino	0.57	0.40	0.83	0.00
Non-latino other	0.70	0.49	1.01	0.06
Education
Not college graduate
College graduate or higher	1.47	1.12	1.92	0.01
Full time employment
No
Yes	0.71	0.55	0.91	0.01
Feelings about household income
Finding it very/difficult on present income
Getting by on present income	1.53	1.08	2.17	0.02
Living comfortably on present income	1.60	1.15	2.22	0.01
Health insurance
Uninsured
Insured	1.02	0.67	1.57	0.92
Unmet need for medical care
No
Yes	0.91	0.73	1.13	0.37
General health
Good/fair/poor
Excellent/very good	1.20	0.82	1.76	0.35
Personal history of cancer
No
Yes	1.50	1.02	2.20	0.04
Family history of cancer
No or not sure
Yes	0.95	0.76	1.18	0.62
Frequency of social media visits
<daily
Daily	0.96	0.73	1.25	0.74
Trust of health care system
High
Low	0.48	0.35	0.66	<0.001
Constant	0.95	0.49	1.84	0.87

The results presented in Appendix Table 1 illustrate the findings from sensitivity analyses using multivariable ordered logit regression to assess the perception of social media health misinformation. The table is divided into two main outcomes: a 3-category outcome and a 5-category outcome. For the 3-category outcome, the coefficient for the perception of substantial health misinformation is −0.27 with a P-value of 0.01, indicating a statistically significant negative association. This means that as the perception of substantial misinformation increases, the likelihood of respondents categorizing their perception as “some & a lot” decreases compared to “almost none & a little” and “don’t know.” Similarly, for the 5-category outcome, the coefficient for substantial misinformation is −0.21 with a P-value of 0.04, also indicating a statistically significant negative association. This implies that higher perceptions of substantial misinformation are associated with a lower likelihood of respondents categorizing their perception as “some” or “a lot” compared to “almost none,” “a little,” and “don’t know.”

As shown in Table 3, this study explored the interaction between perceptions of social media health misinformation/disinformation and the secondary predictor variables on beliefs about progress in curing cancer. For individuals with high trust in the health care system who perceived less than substantial misinformation/disinformation, the predicted probability of believing in progress in curing cancer was 60% (95% CI: 57-63%). When these high-trust individuals perceived substantial misinformation/disinformation, this probability decreased to 53% (95% CI: 48-57%). In contrast, for those with low trust in the health care system, the predicted probability of believing in progress in curing cancer was 42% (95% CI: 32-52%) when they perceived less than substantial mis/disinformation. This probability further decreased to 36% (95% CI: 28-45%) when they perceived substantial misinformation/disinformation. These findings suggest that individuals with high trust in the health care system are more likely to believe in progress in curing cancer, even when they perceive substantial misinformation/disinformation. Conversely, those with low trust exhibit a marked decrease in this belief when they perceive substantial misinformation/disinformation, highlighting the moderating role of health care system trust.

Table 3.

Marginal Effects of Belief That Progress has Been Made in Curing Cancer Estimated From Multivariable Logistic Regression for the Interaction Effect Between Perception of Mis/Disinformation and Health care System Trust and Education, HINTS 6, 2022, N = 4246.

	Margin, %	95% CI
Perception of social media health mis-disinformation x level of health care system trust
< substantial, high trust	60	57-63
< substantial, low trust	42	32-52
Substantial, high trust	53	48-57
Substantial, low trust	36	28-45
Perception of social media health mis-disinformation x frequency of social media use
< substantial, less than daily use	62	56-68
< substantial, daily use	55	51-58
Substantial, less than daily use	44	36-52
Substantial, daily use	53	48-58
Perception of social media health mis-disinformation x education
< substantial, not college graduate	55	51-59
< substantial, college graduate or higher	60	55-65
Substantial, not college graduate	44	39-50
Substantial, college graduate or higher	59	54-65

In addition to exploring the moderating role of trust in the health care system, we examined how the frequency of social media use interacted with perceptions of health mis/disinformation on beliefs about progress in curing cancer. Among respondents who perceived less than substantial misinformation, those who used social media less than daily had a 62% (95% CI: 56-68%) probability of believing that progress has been made in curing cancer. This probability was slightly lower at 55% (95% CI: 51-58%) for daily social media users with the same perception. On the other hand, respondents who perceived substantial misinformation and used social media less than daily had a 44% (95% CI: 36-52%) probability of believing in progress, whereas daily users with the same perception had a higher probability of 53% (95% CI: 48-58%). These findings demonstrate the statistically significant difference between adults that use social media less frequently and perceive substantial misinformation compared to those who use social media less frequently and perceive less than substantial misinformation.

The interaction between educational level and perceived mis/disinformation demonstrated varied impacts on beliefs about cancer progress. Among non-college graduates, the predicted probability of believing progress has been made in curing cancer was 55% (95% CI: 51-59%) among those who perceived less than substantial misinformation/disinformation. Among non-college graduate social media users who perceived substantial misinformation/disinformation, the probability dropped to 44% (95% CI: 39-50%). For college graduates or individuals with higher levels of education, the predicted probability was 60% (95% CI: 55-65%) when they perceived less than substantial misinformation/disinformation, and it remained relatively stable at 59% (95% CI: 54-65%) when they perceived substantial misinformation/disinformation. These results suggest that college graduates maintain a relatively high belief in progress irrespective of their perception of misinformation/disinformation, whereas non-college graduates show a more pronounced low belief in progress when they perceive substantial misinformation/disinformation.

Discussion

Principal Results

This study examined the relationship between attitudes about progress in curing cancer and social media health misinformation and disinformation. We found that adults perceiving substantial health mis/disinformation on social media were significantly less likely to believe that significant progress has been made in curing cancer. This research makes a unique contribution to the literature by being among the first to specifically examine the relationship between perceptions of health misinformation/disinformation on social media and belief in progress in curing cancer. While previous studies have explored the general impact of misinformation on health attitudes, our study introduces the critical moderating effects of trust and education.^5,6 This nuanced approach helps to clarify how these factors influence individual susceptibility to misinformation and shape health beliefs.

The study further delved into the moderating roles of trust in the health care system, frequency of social media use, and educational attainment in the relationship between exposure to health misinformation/disinformation on social media and beliefs about progress in curing cancer. Our findings reveal that high trust in the health care system and higher educational attainment can mitigate the adverse effects of substantial misinformation/disinformation. Notably, higher education levels demonstrate particularly strong resilience against misinformation. The mechanisms through which trust and education impact health beliefs can be multifaceted. High trust in the health care system likely enhances the credibility of information from established medical sources, promoting a more accurate understanding of medical advancements.¹⁹ Trust may lead individuals to seek out reputable sources and adhere to medical advice, reducing the influence of misinformation.^21,22 Education, on the other hand, equips individuals with critical thinking skills and the ability to verify sources, fostering a more nuanced understanding of health information.¹⁶ Educated individuals may be more adept at distinguishing credible information from falsehoods, thereby maintaining informed and optimistic beliefs about medical progress despite exposure to misinformation.^17,18 Finally, individuals who perceived substantial misinformation and used social media less than daily were significantly less likely to believe that progress has been made in curing cancer compared to their counterparts who perceived less substantial misinformation and also used social media less than daily. This result suggests that less frequent social media users might be more susceptible to the negative effects of misinformation, potentially due to a lower overall engagement with and critical consumption of health-related content on these platforms. Daily users, while exposed to substantial misinformation, might also encounter a greater volume of corrective or authoritative health information, which could mitigate the negative impact of misinformation. Alternatively, it could reflect a desensitization effect, where daily users are less swayed by individual pieces of misinformation due to their higher overall exposure to varied content.¹¹

Limitations and Future Research Directions

Despite its strengths, including a nationally representative sample and a comprehensive consideration of variables, we acknowledge certain limitations, including the potential for Neyman bias, also known as incidence-prevalence bias. This bias can occur in cross-sectional studies, where the timing of data collection may affect the representation of individuals with varying degrees of exposure to misinformation. For example, individuals with recent exposure to substantial misinformation may be overrepresented, while those whose views have stabilized over time may be underrepresented. This limitation suggests that our findings may not fully capture the dynamic nature of beliefs and misinformation exposure over time. Future longitudinal research is needed to address this concern by tracking changes in beliefs and misinformation exposure across different time points, thereby providing a more comprehensive understanding of the long-term effects of health misinformation. Moreover, the reliance on self-reported data may introduce recall or social desirability biases, and the dichotomization of certain variables may oversimplify complex constructs although we conducted sensitivity analyses for the outcome variable. Finally, the model did not control for other sources of obtaining health information such as print media or television. Future research should conduct longitudinal studies to track changes in beliefs over time, explore the mechanisms through which trust in the health care system mitigates the impact of mis/disinformation, and identify specific aspects of educational curricula that bolster resilience to health misinformation.

Implications for Practice and Policy

Social media health mis- and disinformation may make it more likely that the public does not believe in public health innovations, such as progress being made in curing cancer. Our findings underscore the importance of cultivating trust in health care institutions and promoting education as strategies to counteract the influence of health misinformation on social media. Public health strategies should prioritize transparency and credibility in health communication, offering regular updates on medical advancements, debunking myths, and clarifying misconceptions.³⁵ This could involve health care systems in local communities providing regular updates about advancements in cancer treatment, debunking common myths, and clarifying misconceptions.^6,36 Promoting education is also essential to mitigate the detrimental impacts of health misinformation.^16,17 Integrating health literacy into educational curricula and offering accessible and comprehensible health information to the public are key strategies.^37,38 Finally, interventions may need to attend to the frequency of social media use with less frequent users potentially more susceptible to social media misinformation.

Conclusion

In conclusion, perception of substantial social media health mis- and disinformation was associated with a lower likelihood of believing progress has been made in curing cancer. Persons that perceived substantial social media health mis-and disinformation and had low trust of the health care system, used social media less frequently, and lacked a college degree were the least likely to believe progress has been made in curing cancer. This study highlights the necessity for a multifaceted approach to counter the influence of health misinformation on social media that includes direct fact-checking and debunking efforts, alongside strategies aimed at enhancing public trust in health care systems and promoting higher education. These findings offer insights for developing tailored interventions to improve public perceptions and foster trust in health care innovations.

Footnotes

Author Contributions

All authors contributed to the study conception and design. Data analysis was performed by JPS. The first draft of the manuscript was written by JPS. All authors contributed to subsequent drafts of the manuscript. All authors read and approved the final version of the manuscript.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: JPS was supported by the National Institute on Minority Health and Health Disparities (NIMHD) at the National Institutes of Health (NIH) under award number R01MD018727. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIMHD. The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Ethical Statement

ORCID iD

Jim P. Stimpson

Data Availability Statement

The Health Information National Trends Survey (HINTS) data used in this study are publicly available from the National Cancer Institute: .

Appendix

Table 4.

Sensitivity Analyses. Multivariable Ordered Logit Regression.

	3 Category Outcome^a		5 Category Outcome^b
	Coefficient	P-value	Coefficient	P-value
Perception of social media health mis-disinformation
<substantial
Substantial	−0.27	0.01	−0.21	0.04

^a3 category outcome: “almost none & a little” = 0, “don’t know” = 1, “some & a lot” = 2.

^b5 category outcome: “almost none” = 0, “a little” = 1, “don’t know” = 2, “some” = 3, “a lot” = 4.

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Belief that Progress has Been Made in Curing Cancer Varies by Perception of Social Media Health Mis- and Disinformation,Education,Frequency of Social Media Use,and Healthcare System Trust: A Cross-Sectional Study

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Methods

Data

Measures

Statistical Analysis

Ethical Considerations

Results

Discussion

Principal Results

Limitations and Future Research Directions

Implications for Practice and Policy

Conclusion

Footnotes

Author Contributions

Declaration of conflicting interests

Funding

Ethical Statement

ORCID iD

Data Availability Statement

Appendix

References