How Does the eHealth Information Use Mitigate Cancer Fatalism in Family Cancer Histories Groups? A Study of Chain Mediation Effects Based on Social Cognitive Theory

doi:10.21203/rs.3.rs-4681352/v1

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Research Article

How Does the eHealth Information Use Mitigate Cancer Fatalism in Family Cancer Histories Groups? A Study of Chain Mediation Effects Based on Social Cognitive Theory

https://doi.org/10.21203/rs.3.rs-4681352/v1

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Background: Cancer fatalism is the greatest obstacle to cancer prevention and treatment behavior and is particularly prevalent among people with a family history of cancer. While previous studies have shown that the use of eHealth information influences cancer fatalism beliefs in the general population, a deeper exploration of the underlying mechanisms is imperative. Using Social Cognitive Theory as a theoretical framework and targeting people with a family history of cancer, this study aimed to investigate whether eHealth information use can effectively alleviate cancer fatalism and elucidate the mechanisms driving this association.

Methods: Data for this study were obtained from the sixth iteration of the National Trends in Health Information Survey (HINTS6), using the survey sample of 3,131 individuals with a family history of cancer. Firstly, this study assesses the direct and indirect effects of eHealth information use on cancer fatalism beliefs; Secondly, exploring the mediating roles of cancer worry, frequency of doctor visits, and trust in cancer information from doctors; Finally, examining a chained mediation model to explain how individuals may change their inherent beliefs about cancer through the eHealth information use.

Results: The results showed that the direct effect (bp =-0.062, p<0.001) and the total effect (bp=-0.059, p<0.001) of eHealth information use were negatively correlated with cancer fatalism. Cancer worry, frequency of doctor visits, and trustin cancer information from doctors were mediating mechanisms and were positively correlated with eHealth information use. In addition, the study revealedthat trustin cancer information from doctors was negatively correlated with cancer fatalism (bp =-0.071, p < 0.001).

Conclusions: eHealth information use combinedwith interventions and offline communication with physicians plays a positive role in reducing cancer fatalism in the family cancer history, providing individuals with more health information and support. Public health departments should use eHealth information platforms to communicate correct cancer science knowledge and positive attitudes toward cancer and encourage people to trust health information from authoritative science, such as doctors, to reduce cancer fatalism and adopt positive health behaviors.

eHealth Information

Cancer Fatalism

Family Cancer History

Social Cognitive Theory

Mediation Model

Many Americans are reported to hold fatalistic beliefs about cancer prevention (i.e., cancer fatalism [1, 2]). The literature defines fatalism using multiple characteristics: a) external events are beyond human control, b) these events are predetermined, and c) as a result, humans feel helpless [3, 4]. Applying this definition to the cancer setting, cancer fatalism refers to the belief that cancer cannot be prevented and that cancer ultimately leads to death [5]. These beliefs are particularly noteworthy because although approximately 45% of men and 38% of women are likely to develop aggressive cancer in their lifetime, nearly half of all cancers are preventable [6, 7]. Furthermore, patients who have undergone active treatment, such as CAR-T cell therapy for the treatment of hematologic malignancies, have shown promising results [8]. Additionally, fatalistic beliefs do not align with recent cancer trends, as cancer incidence has declined in men, and mortality has declined more than both male and female incidence in the United States. The five-year cancer survival rates for most cancers have also improved since 1975 [6].

Eliminating cancer fatalism has been an important public health goal because of its negative impact on both cancer screening and prevention behaviors [5]. Numerous studies have shown that cancer fatalism is a barrier to performing cancer screening tests and engaging in healthy behaviors, including a sensible diet, exercise, and abstinence from smoking and alcohol [9]. More worryingly, cancer fatalism is particularly prevalent in groups with a family history of cancer. Those with a family history of cancer may pay more attention to their risk of developing the disease, and this worry may lead to cancer fatalism [10]. Moreover, some cancer gene mutations may be inherited from parents, and these gene mutations may increase the risk of certain types of cancer [11].

To address these research gaps, this study uses nationally representative survey data to construct a serial mediation model to explore the underlying mechanism of how eHealth information use is associated with cancer fatalism in individuals who have a family history of cancer. Specifically, the proposed mediators include cancer worry, frequency of doctor visits, and trust in cancer information from doctors. eHealth information use can generate cancer-related concerns, which may motivate individuals to seek offline medical inquiries, leading to increased trust in cancer information from doctors and ultimately overcoming the fatalism.

Literature Review and Hypotheses Formulating

Theoretical framework

Social Cognitive Theory (SCT) was developed by Bandura, an American psychologist and the founder of Social Learning Theory. Dr. Lawrance of the Department of Public Health Education of the University of North Carolina [12] pointed out in the 1980s noted that since then, SCT has been gradually applied in the field of health behavior research. For example, studies have analysed the motivation for online health information-seeking behaviors of older adults [13], the influence of personal and social environmental factors on users' health information-seeking behaviors [14], and the factors influencing the perceived social impacts on adolescents' e-justification literacy [15]. In health communication, SCT emphasizes that an individual's health behaviors are influenced by cognition and the environment and that these three factors interact [16]. This study uses these factors to explain how individuals perceive and process health information and how cognitive and environmental factors influence their attitudes and behaviors toward cancer-related issues.

First, SCT can help individuals mitigate cancer fatalism through cognitive processes. Individual cognition refers to an individual's perception of the importance or usefulness of a behavior or event and is tangentially related to an individual's social learning[17] and health-awareness confidence [18]. SCT assumes that an individual's behaviors result from social learning and that through eHealth information platforms such as the internet or social media, learning about cancer is an important process of social learning and cognitive formation. The use of eHealth information creates a certain amount of cancer concern, which prompts people to communicate or inquire more with their doctors, a kind of social learning of interpersonal interaction, and thus is a more positive attitude towards their face of cancer. At the same time, health awareness reflects an individual's psychological orientation toward health and perception of health in daily life, which can influence the individual's perception of the usefulness of health [19]. The use of electronic health information and communication with doctors can help to enhance people's health awareness, and high health awareness will motivate people to actively learn and acquire health-related knowledge and apply it to their daily lives, showing more positive and optimistic attitudes and beliefs [20] and thus alleviating cancer fatalism.

Second, environmental factors in SCT include external role models, external information support, and the influence of significant others [21]. For groups with a family history of cancer, eHealth information use and communication with physicians can be seen as a form of external information support and guidance. On the one hand, individuals can deal with cancer through eHealth information, thereby increasing their health information access and coping strategies and mitigating cancer fatalism [22]. On the other hand, the process of communicating and interacting with doctors with rich medical experience and expertise can provide more authoritative and scientific feedback and guidance to further understand the information needs and outcome feedback of people with a family history of cancer, which can help to alleviate their belief in cancer fatalism. In addition, significant others play an important role in identifying and encouraging the adoption of healthy behaviors. Electronic health information and physicians can also be viewed as significant others, key channels for mimicking the behavior of others or one's own direct experience, thereby influencing individuals' perceptions (e.g., whether they believe the cancer information provided by their physicians) and, ultimately, their attitudes toward cancer fatalism. In the HINTS6 investigation, the application of the theory focuses on the sources of health information: if other people are the key factors in the acquisition of health behaviors by individuals, then the degree of trust in eHealth information and physicians are the key channels for providing cancer-related information, as well as the quality of the information held by various groups in interpersonal communication research. For example, the quality of information held by various groups in interpersonal communication channels varies, as does how to maximize the role of groups that hold quality information, such as doctors and experts, in interpersonal communication. For example, the quality of information held by various groups in interpersonal communication channels varies, and how to maximize the role of groups that hold quality information, such as doctors and experts, in interpersonal communication is one of the questions that needs to be addressed in health intervention activities based on SCT.

eHealth Information Use with Doctor Visits and Cancer Fatalism

Several scholars have begun to explore the effects of health-related media use (primarily mass media use) on cancer fatalism [23]. For example, viewing local television news was found to foster cancer fatalism, whereas no significant associations were observed between viewing national television news, reading newspapers, and cancer fatalism[24].

Unlike most previous studies, the present study focused on the use of eHealth information. Among these, cancer is one of the most widely researched health or medical topics on the Web [25]. A recent study[26] analysed data from two waves of nationally representative surveys and showed that higher levels of health-related internet use in the first wave compared to local television news viewing were expected to decrease. After controlling for possible confounders, the second wave of cancer fatalism [27] provided the following speculative explanation for this result: because internet users almost always have access to a wealth of health and medical information and because the technology offers the possibility of social networking with lay health experts and health professionals [28], internet users can therefore look for up-to-date information about diseases such as cancer and learn about evidence-based prevention recommendations. In addition, by reaching out to numerous other cancer information seekers on the Web, internet users may become aware that many people are actively taking preventive measures to avoid cancer and that proactive behaviors such as online information searching are acceptable and desirable, thus reducing cancer fatalism.

However, a limitation of the study is that the authors viewed health-related internet use as a holistic entity [29]. The internet allows its users to engage in a variety of health-related activities. In addition to reading health or medical information, people can use the internet to purchase medications or vitamins and to find people with similar health problems [30, 31]. To examine the impact of online eHealth information and offline medical consultations on cancer fatalism, the present study employs the unique opportunity of HINTS6 to achieve this goal. More importantly, this study hypothesized that different mediators induced by eHealth information use may be associated with cancer fatalism in different ways. Three types of mediating variables associated with eHealth information use were the focus of this study: cancer worry, frequency of doctor visits, and trust in cancer information from doctors. As previously mentioned, the beneficial effects associated with eHealth information use on cancer fatalism are primarily because users acquire knowledge about cancer either by looking for information themselves online or by switching from online to offline to interact with healthcare professionals such as doctors. Therefore, this study proposes the following hypotheses:

H1. eHealth Information Use has a direct effect on alleviating Cancer Fatalism.

H2. eHealth Information Use has a positive effect on the Frequency of Doctor Visits.

The Possible Role of eHealth Information Use in Trusting Physicians

In addition, we explored the role that eHealth information use may play in terms of trust in cancer information from physicians. Many scholars [26] have demonstrated that individuals rely on cognitive shortcuts or heuristics (e.g., trust) to compensate for a lack of knowledge during the decision-making process. their lack of knowledge (e.g., medical or health issues). Trust has been defined as "the principal's expectation that the trustee can be trusted and that interactions with the trustee will increase the likelihood that the principal will gain rather than lose" [32]. A large body of communication research has long shown that, as rational beings, individuals tend to choose trusted sources of information from an increasing number of available resources in the information environment [32]. This relationship has also been confirmed in the field of public health. For example, people who trust healthcare professionals, such as physicians, are more likely to ask them questions and seek answers than people who do not trust them [33]. Similarly, concerning patient trust in physicians, several studies have shown that news stories about cancer enhance audience trust in scientists and physicians associated with the topic. Most notably, Jensen conducted an experimental study on news coverage of cancer and found that news increased participants' trust in experts [23]. To understand the audience's perceptions of healthcare professionals in general, Jensen replicated a previous study revisiting the relationship between news hedging and several cognitive constructs[23], including patient trust in healthcare professionals, and their results were consistent with previous findings. In a similar vein, eHealth information acts similarly to cancer news and has an impact on whether or not patients trust cancer information from physicians. Therefore, this study hypothesizes the following:

H3. eHealth Information Use has a positive effect on Trust in Cancer Information from Doctors.

Causes, effects, and coping strategies of cancer worry

Cancer worry is a common phenomenon characterized by negative thoughts about cancer and concerns about an individual's susceptibility to the disease [34]. It has been suggested in the literature that online health information provides insights into risk factors, symptoms, and preventative measures that raise concerns about an individual's susceptibility to cancer [29]. Consistent with this, analysis of previous HINTS data suggested that the use of eHealth information elicits some degree of personal health concerns and cancer concerns due to a family history of cancer for a variety of specific reasons [35]. Therefore, this study hypothesized the following:

H4. eHealth Information Use contributes in part to Cancer Worry.

However, cancer worry can also lead to a state of negative uncertainty, and in more severe cases, pessimism, such as cancer fatalism, which is detrimental to cancer prevention and treatment, needs to be reduced through coping strategies [36]. Individuals who are worried and anxious about their health tend to seek more authoritative information and medical resources to find evidence to support their concerns [37]. As mentioned in the theoretical framework above, offline communication with physicians as a social support factor is the primary evidence for alleviating or confirming cancer concerns. Patients suffering from diseases such as cancer usually consider clinicians to be relevant references who can accompany and support them in coping with the disease [38]. Physicians provide social support through encouragement, counselling, and advocacy in patient‒physician interactions [15]. Therefore, this study proposes the following hypotheses:

H5. Cancer Worry reinforces Cancer Fatalism.

H6. Cancer Worry may increase the frequency of doctor visits.

It is easy to see that cancer worry is inevitable after using eHealth information and that different measures taken in response to this psychological factor produce different results: cancer worry is likely to develop further into cancer fatalism if no coping strategies are used, and cancer fatalism is likely to be reduced if help and validation are sought from a doctor or a specialist. As noted earlier and in the theoretical framework, physicians, such as SIGNIFICANT OTHERS, are key channels for mimicking the behaviors of others or one's own direct experience [22]. Individuals may deal with cancer through offline visits to the doctor, thus proving whether their concerns are misplaced to reduce their fatalism about cancer [29]. Therefore, this study proposes the following hypotheses:

H7. A greater frequency of doctor visits is likely to mitigate Cancer Fatalism.

The Effect of Trusting Cancer Information from Doctors on Cancer Fatalism

From the perspective of SCT, the frequency of doctor visits can influence individuals' perceptions (e.g., whether or not they trust cancer information from doctors) and ultimately their attitudes toward cancer fatalism. If others are the key factors for individuals to acquire health behaviors, then the degree of trust in cancer information and the quality of information possessed by doctors, as the key channel for providing cancer-related information, are questions that need to be answered in health communication research[22]. For example, the quality of information held by various groups in interpersonal communication channels varies, and how to maximize the role of groups such as doctors and experts who hold high-quality information in interpersonal communication is one of the issues that needs to be focused on in health intervention activities based on SCT [22]. Some studies have shown that changes in patient roles seem to be related to patients' information-seeking behaviors, which may affect the patient‒physician relationship. More specifically, patients perceive medical practitioners as the most trusted source of health information, especially regarding cancer[39]. Therefore, this study hypothesizes the following:

H8. The frequency of doctor visits increases Trust in Cancer Information from Doctors.

Previous studies have shown that the relationship between men's experiences of uncertainty about prostate cancer and their levels of trust in doctors and fatalistic beliefs may also vary according to several socioeconomic factors. Findings have also suggested that patients' fatalistic beliefs about cancer are related to trust in healthcare professionals [40]. Cancer fatalism refers to the belief that nothing can be done to prevent or treat cancer [5, 23]. According to uncertainty reduction theory and anxiety-uncertainty management, some scholars have argued that two key functions of health communication are information seeking and anxiety reduction [41]. Individuals manage their uncertainty and corresponding negative emotions by purposefully seeking health information [41]. Additionally, communicating with and trusting one's doctor helps to alleviate psychological factors such as cancer worry and cancer fatalism. Although individuals attempt to reduce uncertainty by seeking new information, their efforts may not always be successful [42]. Therefore, this study hypothesizes the following:

H9. Trusting cancer information from doctors may alleviate Cancer Fatalism.

Combining the above literature review and research hypotheses, Fig. 1 presents the conceptual model for this study.

Sample

The data are from the sixth iteration of the National Cancer Institute's (NCI) National Trends in Health Information Survey (HINTS6) (http://hints.cancer.gov/). The Health Information National Trends Survey (HINTS) is a nationally representative survey that has been administered every few years by the National Cancer Institute since 2003. The HINTS target population is all adults aged 18 or older in the civilian noninstitutionalized population of the United States. The HINTS program collects data on the American public's need for, access to, and use of health-related information and health-related behaviors, perceptions, and knowledge [31].

Data collection for HINTS6 started on March 7, 2022, and concluded on November 8, 2022. Starting with HINTS 6, the data will be collected on a biennial basis. HINTS 6 draws upon the lessons learned from prior iterations of HINTS and incorporates an experimental design. A multimode survey was implemented using paper and web modes. The respondents were randomly assigned to one of two groups: 1) Concurrent: they were offered the two modes at the same time (web and paper); or 2) Sequential: they were offered one mode first (web) and the other mode later (paper). Details about the protocol for this mixed-mode experiment are provided in the Methodology Report.

The final HINTS6 sample consisted of 6,252 respondents. Of these, 4,611 respondents were in the concurrent group, and 1,641 were in the sequential group. Household response rates were calculated using the American Association for Public Opinion Research response rate 4 (RR4) formulas. The overall household response rate using the next-birthday method was 28.1%. More specifically, the overall response rate of the concurrent group was 29.1%, and that of the sequential group was 25.8%.

Measurement

Table 1

provides descriptive statistics for all variables. The specific measurements are shown below:
Table 1		Raw Scales (n_s) (observed)				Conceptual Range		01 Percentage Scales (p_s) (observed)
	n = 3131	Min	Max	Ave	SD	Min (c_n)	Max (c_x)	Min	Max	Ave	SD
1.	CF	1.00	4.00	2.34	0.69	1.00	4.00	0.00	1.00	0.45	0.23
2.	EIU	0.00	1.00	0.73	0.32	0.00	1.00	0.00	1.00	0.73	0.32
3.	CW	1.00	5.00	2.80	1.18	1.00	5.00	0.00	1.00	0.45	0.29
4.	FDV	0.00	6.00	3.10	1.82	0.00	6.00	0.00	1.00	0.52	0.30
5.	TCID	1.00	4.00	3.69	0.59	1.00	4.00	0.00	1.00	0.90	0.20
6.	EDU	1.00	7.00	5.12	1.54	1.00	7.00	0.00	1.00	0.69	0.26
7.	GEN	0.00	1.00	0.63	0.48	0.00	1.00	0.00	1.00	0.63	0.48
8.	AGE	18.00	97.00	57.23	16.79	18.00	97.00	0.00	1.00	0.50	0.21
9.	INC	1.00	9.00	5.79	2.23	1.00	9.00	0.00	1.00	0.59	0.27

The dependent variable (Table 2), Cancer Fatalism(CF), is based on the three questions below (Cronbach’s α = .67). The respondents answered the following statements on a 4-point Likert-type scale ranging from strongly agree to strongly disagree: “It seems like everything causes cancer” (Belief 1), “There’s not much you can do to lower your chances of getting cancer” (Belief 2), and “When I think about cancer, I automatically think about death” (Belief 3). The fatalism items are unique to the HINTS surveys; they have been used in multiple years and show predictive capability for cancer preventive health behaviors [24]. Agreement was defined as strongly agree or somewhat agree [24]. The CF values coded 1 to 4, where 1 indicates that a respondent has a very negative attitude towards cancer (cancer fatalism) and 4 indicates that the respondent has a very positive and optimistic attitude towards cancer (Mean = 2.34, SD = 0.69).

Table 2

Specific details of the key variable CF *Cancer Fatalism*,
Q. P3: How much do you agree or disagree::	Strongly agree	Somewhat agree	Somewhat disagree	Strongly disagree	Non Valid	Total
Right: coding	4	3	2	1	Miss.
P3a. It seems like everything causes cancer…	20.5	44.2	21.7	12.4	1.2	100
P3b. There’s not much you can do to lower your chances of getting cancer…	6.7	20.2	41.2	31.1	1.2	100
P3c. There are so many different recommendations about preventing cancer, its hard to know which ones to follow…	19.5	47.2	22.2	9.8	1.4	100
P3d. When I think about cancer, I automatically think about death…	19.2	35.4	27.3	17.3	1.1	100

The independent variable (Table 3), eHealth Information Use (EIU), was based on HINTS data measured as internet Use for DWPA in a previous study [43]. The following questions were combined with four items (Cronbach’s α = .724). “In the past 12 months have you used the internet to: a. Look for health or medical information? b. send a message to a health care provider or health care providers office? c. view medical test results? d. make an appointment with a health care provider?” The measurement ranges for each item are “0 = NO and 1 = YES”, where 0 indicates that the respondent did not use electronic devices to access health information in the past year, whereas 1 indicates that the respondent used electronic devices to access health information in the past year. (Mean = 0.73, SD = 0.32).

Table 3

Specific details of the key variable, EIU *eHealth Information Use*
Q. B3. In the past 12 months have you used the Internet to…	NO	YES	Non valid	Total
Coding	0	1	Miss.
B3a. Look for health or medical information?	10.8	73.4	15.8	100
B3b. send a message to a health care provider or health care providers office?	27.3	56.8	15.9	100
B3c. view medical test results?	21.7	62.2	16.1	100
B3d. make an appointment with a health care provider?	30.5	53.7	15.8	100

Mediator 1 (Table 4), Cancer Worry (CW), was measured from one item asking the respondents how worried they were about getting cancer [44]. The responses were rated on a 5-point Likert scale (from 1= “not at all” to 5= “extremely”), where 1 indicated respondents had never worried about cancer, and 5 indicated respondents were extremely worried about cancer (Mean = 2.62, SD = 1.22).

Table 4

Specific details of the key variable CW *Cancer Worry*
Q. P1. How worried are you about getting cancer?	Not at all	Strongly	Somewhat	Moderately	Extremely	Non Valid	Total
Right: coding	1	2	3	4	5	Miss.
Percent	14.7	27.2	30.2	17.3	9.8	0.8	100

Mediator 2 (Table 5), Frequency of Doctor Visits(FDV), was based on HINTS data measured as the frequency of visiting a provider in a previous study [45]. FDV was measured from one item asking the respondents “In the past 12 months, not counting times you went to an emergency room, how many times did you go to a doctor, nurse, or other health professional to get care for yourself?” The responses were rated on a scale of “0 = None to 6 = 10 or more times”, where 0 indicates that the respondent has never seen a doctor in the past 12 months, the frequency of doctor visits increases with the coding number, and 6 indicates that the respondent has seen a doctor 10 or more times in the past 12 months (Mean = 3.10, SD = 1.28).

Table 5. Specific details of the key variable FDV

Mediator 3 (Table 6), Trust in Cancer Information from Doctors (TCID), is based on the question “In general, how much would you trust information about cancer from a doctor [46] ” The responses were rated on a 4-point Likert scale (from 1= “not at all” to 4 = “A lot”), where 1 indicates that respondents do not trust cancer information from doctors and 4 indicates that respondents have a great deal of trust in cancer information from doctors (Mean = 3.69, SD = 0.59).

Table 6

Specific details of the key variable TCID *Trust in Cancer Information from Doctors*
Q. A3a. In general, how much would you trust information about cancer from a doctor?	A lot	Some	A little	Not at all	Non Valid	Total
Right: coding	4	3	2	1	Miss.
Percent	73.5	20.6	3.5	1.0	1.3	100

The control variables (Table 7) consisted of the demographic variables of age(Mean = 57.23, SD = 16.79, Min = 18, Max = 97) gender(1 = female, 0 = male, Mean = 1.64, SD = 0.48), education(Mean = 5.12, SD = 1.54, Min = 1, Max = 7), and annual household income(Mean = 5.79, SD = 2.23, Min = 1, Max = 9) to minimize the potential influence of confounding factors on cancer fatalism.

Table 7

Specific details of the control variables
Characteristic	Value
Gender, n (%)
Male	1439 (36.2%)
Female	2541 (63.8%)
Age in years, mean (SD)	57.23 (16.79)
Education, n (%)
Less than 8 years	47(1.2%)
8 through 11 years	149(3.7%)
12 years or completed high school	680(17.1%)
Post high school training other than college	294(7.4%)
Some college	850(21.3%)
College graduate	1152(28.9%)
Postgraduate	810(20.3%)
Household annual income (USD), n (%)
$0 to $9,999	223(5.9%)
$10,000 to $14,999	187(5.0%)
$15,000 to $19,999	159(4.2%)
$20,000 to $34,999	464(12.3%)
$35,000 to $49,999	502(13.3%)
$50,000 to $74,999	665(17.7%)
$75,000 to $99,999	491(13.0%)
$100,000 to $199,999	735(19.5%)
$200,000 or more	340(9.0%)
N	3131

Data analysis

CW, FDV, and TCID are three chained mediation variables, CF is the dependent variable, and EIU is the independent variable. People with a family history of cancer were selected for this study. Cases with invalid responses were listed as missing values, resulting in a final sample size of 3131. Among them, the dependent variable CF, the independent variable EIU, and the mediator variable TCID were recoded to ensure that larger values represented higher degrees and were easy to understand and interpret.

IBM SPSS Statistics 26.0 was used for the statistical analysis. Initially, descriptive analysis was performed to summarize the characteristics of the key variables. Subsequently, a Pearson correlation test was performed to examine the relationships between the key variables. Furthermore, the SPSS macro PROCESS (v4.3) [47] model 6 was used to determine the serial mediating effects of CW, FDV, and TCID on the association between EIU and CF. To facilitate the analysis, all variables in this study were transformed according to the normalization of 0 (minimum concept value)-1 (maximum concept value), and the unit of variable value was unified into a percentage. On this basis, the regression coefficient obtained is called the "percentage coefficient", referred to as "bp", so that there is comparability among variables [48]. Statistical assessment of effects included p values, and the analysis was further validated through bootstrapping (5,000 samples) with 95% confidence intervals (CIs) [44].

Preliminary Analysis

As shown in Tables 1 and 7, 63.8% of the respondents with a family history of cancer were females, whereas 36.2% were males. The average age of the respondents was 57 years. In addition, approximately 70% of the respondents had a college degree or higher. The largest number of respondents (75.8%) had an annual household income between US$20,000 and US$199,999. The majority of respondents (73.4%) had access to the internet to look for health or medical information, and the majority of respondents indicated that they strongly or somewhat agreed with cancer fatalism. Only 14.7% of respondents were not worried about getting cancer. Most respondents with a family history of cancer (73.5%) strongly trust information about cancer from their doctor.

As shown in Table 8, the Pearson correlation findings revealed significant associations between most of the key variables.

Table 8. Zero-order Pearson Correlations (n = 3131)
Variables	1.CF	2 .EIU	3.CW	4.FDV	5 .TCID	6 .EDU	7 .GEN	8.AGE	9. INC
1.CF	—	-.087^**	.198^**	-.041^*	-.096^**	-.231^**	.013	-.173^**	-.151^**
2.EIU		—	.082^**	.190^**	.108^**	.272^**	.038^*	-.180^**	.279^**
3.CW			—	.112^**	.059^**	-.024	.029	-.061^**	.011
4.FDV				—	.106^**	.057^**	.088^**	.157^**	.009
5.TCID					—	.116^**	-.014	-.015	.166^**
6.EDU						—	-.022	-.129^**	.483^**
7.GEN							—	-.029	-.134^**
8.AGE								—	-.152^**
9.INC									—
p<.05; *p<.01

Hypothesis Analysis

Figure 2 and Table 9 present the results of the regression analysis of the serial mediator model for the effect of EIU on CF mediated by CW, FDV & TCID. where bp stands for the percentage coefficient, *p < .05, **p < .01, ***p < .001, and below are the specific analyses and illustrations.

Table 9. Summary of mediation effects	*b_p*	β	SE	95%Boot CI	*p^a*
DV: Cancer Fatalism
EIUeàCW (apath)	.063	.286	.017	[.036, .105]	<.001
EIUà FDV (gpath)	.206	.220	.017	[.186, .254]	<.001
CWà FDV(bpath)	.078	.157	.017	[.066, .136]	<.001
EIUàTCID (hpath)	.081	.113	.011	[.008, .052]	.006
FDVàTCID (e path)	.183	.022	.011	[.021, .065]	<.001
CWà CF (jpath)	.149	.111	.013	[.126, .177]	<.001
FDVà CF (ipath)	-0.01	.005	.013	[-.019, .032]	.599
TCIDà CF (f path)	-.071	-.076	.021	[-.113, -.033]	<.001
EIU à CF(direct effect, d path)	-.062	-.186	.013	[-.086, -.036]	<.001
EIU à CF (total effect, c path)	-.059	-.159	.013	[-.077, -.027]	<.001
EIUàCWà CF (indirect effect, aj)	.011	0.32	.003	[.005, .017]	/
EIUàTCIDà CF (indirect effect, hf)	-.002	-.009	.001	[-.005, -.000]	/
EIUàFDVà TCIDà CF (indirect effect, gef)	-.001	-.002	.000	[-.001, -.000]	/
EIUàCWà FDVàTCIDàCF (indirect effect, af)	.000	-.000	.000	[.000, .000]	/

^ap-values are not computed for bootstrapped indirect effects.

Hypothesis 1 proposed a direct effect of eHealth Information Use on alleviating Cancer Fatalism. The data analysis revealed a significant negative association between EIU and CF, with a regression coefficient (bp = -0.06, b=-0.19, p <.001). Thus, H1 was supported.

Hypothesis 2 suggested that eHealth Information Use contributes in part to Cancer Worry. The data analysis revealed a significant positive association between EIU and CW, with a regression coefficient (bp = 0.06, b=0.29, p <.001). Thus, H2 was supported.

Hypothesis 3 posited a positive effect of eHealth Information Use on the Frequency of Doctor Visits and Cancer Information Trust from Doctors. The data analysis revealed significant positive associations between EIU and both FDV (bp=0.21, b=0.22, p <.001) and between EIU and TCID (bp= 0.08, b=0.11, p=.006). Thus, H3 was supported.

Hypothesis 4 proposed that cancer worry reinforces Cancer Fatalism. The data analysis revealed a significant positive association between CW and CF (bp = 0.15, b=0.11, p <.001). Thus, H4 was supported.

Hypothesis 5 suggested that cancer worry may increase the frequency of doctor visits. The data analysis showed that higher levels of cancer worry were associated with an increased frequency of doctor visits, revealing a significant positive association between CW and FDV, with a regression coefficient (bp) of 0.08 (b=0.16, p <.001). Thus, H5 was supported.

Hypothesis 6 proposed that a greater frequency of doctor visits mitigates Cancer Fatalism. However, the data analysis did not reveal a significant association between FDV and CF (bp = -0.01, b=0.01, p > .05). Thus, H6 was rejected.

Hypothesis 7 suggests that the frequency of doctor visits increases cancer information trust from doctors. The data analysis revealed a significant positive association between FDV and TCID, with a regression coefficient (bp = 0.18, b=0.02, p <.001). Thus, H7 was supported.

Hypothesis 8 proposed that trusting cancer information from doctors may alleviate Cancer Fatalism. The data analysis showed that showing a significant negative association between TCID and CF (bp =-0.07, b=-0.08, p <.001). Thus, H8 was supported.

Hypothesis 9 examined the total effect of eHealth Information Use on Cancer Fatalism. The analysis revealed a significant negative total effect (bp = -0.06, b=-0.16, p <.001). Thus, H9 was supported.

Summary of research findings

The purpose of this study was to examine the mitigating effects of using eHealth information on cancer fatalism in a family cancer group with a chain-mediated effect based on SCT. The data analysis and findings indicated significant associations between eHealth information use, frequency of doctor visits, trust in cancer information from doctors, cancer worry, and cancer fatalism, and the research hypotheses were tested one by one. Cancer fatalism in individuals with a family history of cancer can be effectively mitigated through eHealth information use. The mediating variable of trust in cancer information from doctors plays a crucial role in this process, as it enhances individuals' perception of the scientific validity and accuracy of the cancer information they receive and reduces their feelings of helplessness and predetermined outcomes associated with cancer fatalism. These findings are consistent with those of SCT, which emphasizes the importance of information access and trust in physicians in shaping individuals' attitudes and behaviors toward cancer. These findings have important implications for improving patients' mindsets in the face of cancer and promoting cancer prevention and treatment behaviors.

Elaboration of key findings and research results

First, the use of eHealth information has a direct impact on mitigating cancer fatalism, with higher levels of eHealth information use being associated with lower levels of cancer fatalism, suggesting that through the use of eHealth information, individuals in the cancer family history group can reduce their beliefs about cancer fatalism. This finding underscores the importance of eHealth information as an effective way to change perceptions of cancer and promote positive health behaviors.

Second, the use of eHealth information somewhat increases patients' cancer concerns. The results of the data analysis revealed a significant positive association between the use of eHealth information and cancer worry. This finding reminds us that patients may experience a certain degree of worry after using eHealth information, which may further exacerbate their beliefs about cancer fatalism, thus adversely affecting cancer prevention. Therefore, if cancer concerns arise after using eHealth information, patients need to seek medical help offline to further confirm their health status and the veracity of their online cancer information.

Third, the use of eHealth information had a positive impact on visits to doctors and patients’ trust in the cancer information provided by doctors. The results of the data analysis showed that there was a significant positive association between the use of eHealth information and the frequency of doctor visits and trust in doctor-provided cancer information. This suggests that through the use of eHealth information, individuals have stronger hospital line visits to doctors and more trust in the cancer information provided by the doctor. This finding is in line with previous studies showing that eHealth information use improves patients' eHealth literacy, which leads to greater trust in physicians [49]. This provides an opportunity for the cancer family history group to develop a stronger relationship with their physicians, leading to better engagement in cancer prevention and treatment.

Fourth, there was a positive association between cancer worry and cancer fatalism. This means that individuals with a family history of cancer are more likely to hold fatalistic beliefs about cancer after worrying about cancer as a result of using eHealth information without intervention. The literature also proves this point and highlights the reasons for it. For example, analysis of HINTS data previously indicated that the use of electronic health information has caused concerns about personal health problems and cancer problems to some extent for various specific reasons [39]. Online health information provides insights into risk factors, symptoms, and preventive measures regarding an individual's susceptibility to cancer [29]. This finding illustrates that although eHealth information use can help mitigate cancer fatalism, it can also increase cancer worry. If patients are simply exposed to eHealth information without intervention, they are likely to develop anxiety and fantasies about the disease, which requires the intervention of healthcare professionals such as physicians to help alleviate their worries and change their fatalistic beliefs about cancer.

Fifth, there was a positive association between cancer worry and the frequency of doctor visits. This suggests that individuals in the cancer family history group are more inclined to seek medical care more frequently when faced with cancer-related worries. As previous research has pointed out, individuals may deal with cancer through offline visits to doctors, thus proving whether their concerns are misplaced to reduce their fatalism about cancer [29]. However, our study also revealed that hypothesis 6 did not hold in the data of this study and that increasing the frequency of doctor visits did not directly alleviate cancer fatalism. This result suggests that simply increasing the frequency of doctor visits may not be sufficient to change an individual's fatalistic conception of cancer and that more trust in the advice and information given by doctors and following a scientific approach to facing cancer is needed [50].

Sixth, there was a positive association between the frequency of doctor visits and trust in cancer information provided by doctors. Through data analysis, we found that people with a greater frequency of medical visits were more likely to trust cancer information from doctors. This is consistent with this study's advocacy of encouraging the idea of seeking help from doctors for more scientific and accurate information in the face of cancer. The quality of information held by various groups in interpersonal communication channels varies, and how to maximize the role of groups such as doctors and experts who hold high-quality information in interpersonal communication is one of the issues that needs to be focused on in health intervention activities based on SCT [22]. This result emphasizes the importance of a good trusting relationship between physicians and patients, with physicians playing a key role in providing accurate and reliable cancer information.

Finally, trusting cancer information from physicians can help alleviate cancer fatalism. The results of the data analysis supported this hypothesis by showing a negative association between trust in cancer information provided by physicians and cancer fatalism. This means that the more trust an individual has in the cancer information provided by their doctor, the lower their belief in cancer fatalism. This finding emphasizes the importance of physicians providing accurate and trustworthy cancer information to help individuals develop positive health beliefs.

Practical significance and academic value of the study

From a practice perspective, this study has practical implications for public health policymakers, healthcare providers, and the media, providing an important reference for the development of health policies and interventions targeting groups with a family history of cancer. This study suggested that interventions using eHealth information to increase trust in physicians could be effective in mitigating cancer fatalism. Given the significant impact of eHealth information use on public health perceptions and behaviors, public health authorities and mass media must make full use of eHealth information channels for health literacy and education. For instance, by understanding the impact of eHealth information on cancer attitudes and doctor-seeking behaviors, patients are encouraged to seek help from doctors and specialists when they face cancer problems and to trust authoritative scientific information about cancer to dispel cancer-related misconceptions and fears.

This study also makes several important theoretical contributions. Firstly, this study extends previous social cognitive theory and its derived models by focusing on the relationship between eHealth information use—a psychological and behavioral mediator—and cancer fatalism, providing additional empirical support for the applicability of SCT in the context of health communication. Secondly, the model of this study provides a theoretical framework for understanding how people with a family history of cancer practice health management and develop positive health beliefs in the internet era. Using eHealth information can help improve the threat to cancer awareness, promote timely medical treatment, and increase trust in scientific information from doctors and other professionals to improve the belief of cancer fatalism. Finally, this study helps to fill the gap in understanding the impact of eHealth information on cancer fatalism in groups with a family history of cancer and provides a foundation and new research directions for future studies in this area. At the same time, the study emphasizes the importance of interventionists’ use of eHealth information and the importance of choosing to see a doctor when faced with cancer concerns and trusting the cancer information provided by the doctor in health communication research.

Study limitations and future research directions

Despite the important findings of this study, there are some limitations worth acknowledging. First, this study relies on self-reported data and a cross-sectional design, which limits the identification of causal relationships between key variables. Future studies could explore study designs with longitudinal data or experiments and conduct comparative analyses using longitudinal data to assess the long-term effects of eHealth information use on cancer fatalism and health behaviors. Second, the relatively small sample size may limit the generalizability of the results. Future research could consider expanding the sample size and employing more diverse research methods, such as a mixed method combining qualitative and quantitative methods, to further validate and deepen the results of this study. Third, measures of eHealth information use have focused on general health information, and follow-up surveys should specifically assess the impact of health information related to cancer or cancer fatalism. In addition, multiyear data can be used to conduct comparative cross-year analyses to further explore the mechanisms underlying the impact of eHealth information on cancer fatalism, thus providing more useful insights into the development of related fields.

Eliminating or mitigating cancer fatalism-related mortality is essential for the prevention and active treatment of cancer. Individuals with a family history of cancer tend to have more severe cancer fatalism. However, prior research has paid little attention to the role of eHealth information use in mitigating cancer fatalism in family cancer history groups. The present study revealed that although eHealth information use may reduce patients' cancer fatalism beliefs, it may also cause a certain degree of cancer worry in the absence of interventions, which in turn may exacerbate cancer fatalism to the detriment of cancer prevention. Therefore, if cancer worry emerges after using eHealth information, patients need to seek help from doctors offline to further confirm their health status and the authenticity of online cancer information. However, the results of this study show that simply increasing the frequency of doctor visits will not directly alleviate cancer fatalism. Patients need to visit their doctors, trust cancer information from their doctors more, discard incorrect eHealth information, and follow their doctor's instructions for positive action and treatment to effectively alleviate cancer fatalism. These findings emphasize the potential importance of eHealth information in helping individuals with a family history of cancer cope with the challenges of cancer and provide useful insights for future health communication and cancer interventions.

SCT

Social Cognitive Theory

HINTS

National Trends in Health Information Survey

Cancer Fatalism

EIU

eHealth Information Use

Cancer Worry

FDV

Frequency of Doctor Visits

TCID

Trust in Cancer Information from Doctors

EDU

Education

GEN

Birth Gender

AGE

Age

INC ($K)

Household Income

Author contributions

JZW conceived and proposed the model for this study, performed the data processing and analyses, and made significant contributions to the writing of the manuscript.QRL improved the model and provided extensive guidance throughout the writing and revision of the manuscript.XSZ acted as the project leader and corresponding author, and performed the final review of the manuscript, overseeing and ensuring the integrity of the study. All authors carefully read and approved the final manuscript.

Funding

This research was supported in part by grants of the University of Macau, including CRG2021-00002-ICI, ICI-RTO-0010-2021, CPG2023-00003-FSS, Xinshu Zhao PI; Macau Higher Education Fund, HSS-UMAC-2020-02, Xinshu Zhao PI.

Data availability

The datasets generated and/or analysed during the current study are available

in the open access repository, via http://hints.cancer.gov/.

Declarations

Ethics approval and consent to participate

The HINTS data meet established ethical standards and have obtained ethics approval.

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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No competing interests reported.

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How Does the eHealth Information Use Mitigate Cancer Fatalism in Family Cancer Histories Groups? A Study of Chain Mediation Effects Based on Social Cognitive Theory

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Abstract

Figures

Introduction

Literature Review and Hypotheses Formulating

Theoretical framework

eHealth Information Use with Doctor Visits and Cancer Fatalism

The Possible Role of eHealth Information Use in Trusting Physicians

Causes, effects, and coping strategies of cancer worry

The Effect of Trusting Cancer Information from Doctors on Cancer Fatalism

Method

Sample

Measurement

Data analysis

Results

Discussion

Summary of research findings

Elaboration of key findings and research results

Practical significance and academic value of the study

Study limitations and future research directions

Conclusion

Abbreviations

Declarations

References

Additional Declarations

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