Coping self-efficacy influences health information avoidance

Abstract

Avoiding information about one’s health can have long-term implications for health and well-being. Two studies examined the relationship between health information avoidance and coping self-efficacy, or a sense that one can effectively cope. In Study 1, coping self-efficacy, but not general self-efficacy, was associated with information avoidance. In Study 2, participants who reflected on their positive coping strategies were less likely to avoid learning their risk for disease as compared to those who did not reflect on their coping strategies. These findings suggest that coping self-efficacy is a good target for future interventions aimed at reducing health information avoidance.

Keywords

coping health behavior information risk self-efficacy

Introduction

Despite widespread efforts to reduce the prevalence of diabetes by the Office of Disease Prevention and Health Promotion, diabetes remains one of the leading causes of death in the United States (Heron, 2018). Of 136 million adults who met the American Diabetes Association criteria for being screening-recommended, only 46.2% reported screening in the last 3 years (Kiefer et al., 2015). Some may assume that the decision to forego screening is due to structural factors such as lack of access to healthcare. Nevertheless, of those who reported not screening, 76.1% were insured (Kiefer et al., 2015). This suggests that decisions to forego diabetes screening may be driven by other psychosocial factors.

The decision not to screen for disease falls under the broader label information avoidance. Information avoidance refers to any behavior aimed at preventing the acquisition of available information (Sweeny et al., 2010). In health contexts, information avoidance can manifest in decisions to avoid risk assessments and screening for disease. In one study, 30% of a college student sample chose to avoid viewing a UV photograph that could reveal their skin damage (Dwyer et al., 2015). In another study, 39% of a US-representative adult sample reported they would rather not know their lifetime risk of developing cancer (Emanuel et al., 2015). Given that early detection and diagnosis are key to better long-term health outcomes (Herman et al., 2015; Levin and Stevens, 2011; Weimer and Sager, 2009), it is important to identify ways to decrease health information avoidance.

Causes of information avoidance

Past research suggests three underlying motivators for health information avoidance: perceived threat to beliefs, affect, and behavior (Howell et al., 2016; Shepperd and Howell, 2015). First, people may avoid health information to maintain cherished beliefs about their identity. Research on selective exposure demonstrates that people tend to seek information that affirms their pre-existing beliefs and to avoid information that challenges their beliefs (Hart et al., 2009; Smith et al., 2008). For example, in one study, participants were more inclined to avoid viewing a UV photograph of their skin damage if they believed the photograph would show them as ugly (Dwyer et al., 2015). The second reason people avoid information is to maintain positive emotions and to avoid negative emotions (Shepperd and Howell, 2015). For instance, multiple studies suggest that people will avoid information such as risk for breast cancer and whether one’s marriage will end in divorce if they believe they will regret learning that information (Gigerenzer and Garcia-Retamero, 2017; Melnyk and Shepperd, 2012). The third reason people avoid information is that they think it might obligate them to engage in undesired behaviors (Shepperd and Howell, 2015). For instance, women in one study were more receptive to learning their risk for a disease if definitive testing for the disease involved a cheek swab as opposed to a cervical examination (Howell and Shepperd, 2013).

Information avoidance and coping

The cognitive, affective, and behavioral underpinnings of information avoidance point to a broader factor underlying avoidance: a sense that one cannot cope with the cognitive, affective, and behavioral implications of bad news. For example, in one study, participants reporting fewer personal/coping and interpersonal/social support resources were more likely to avoid learning their risk for disease (Howell et al., 2014). Another study demonstrated that experiencing social rejection—which was hypothesized to produce a decrement in social coping resources—caused increased avoidance of health screening feedback (Howell and Shepperd, 2017).

Related to work implicating a sense that one can cope in information avoidance, is evidence linking perceptions of personal control—the perception that one has the ability to regulate their disease outcomes—to decreased information avoidance. For example, people avoid learning their risk/disease status more often when a disease is treatable than when it is untreatable (Howell and Shepperd, 2013). Similarly, participants in one study were less likely to request genetic testing for untreatable medical conditions as compared to treatable medical conditions (Dawson et al., 2006). Additionally, emphasizing the controllable aspects of a disease can reduce avoidance. In one study, women who learned about uncontrollable predictors of breast cancer were more likely to avoid learning their risk than women who learned about controllable predictors (Melnyk and Shepperd, 2012). Taking together evidence that coping resources matter with the evidence that a lack of control spurs information avoidance, we propose a novel factor that may underlie information avoidance: a lack of coping self-efficacy.

Self-efficacy

Self-efficacy theory posits that responses to challenges depend on personal self-efficacy, or one’s judgment about their ability to accomplish goals (Bandura, 1977). Furthermore, people draw self-efficacy from four sources: vicarious learning, mastery experiences, physiological states, and verbal persuasion (Bandura, 1977). Vicarious learning refers to gaining self-efficacy by observing others’ successes and failures. When one sees a similar other succeed, one feels more capable of personally succeeding. Mastery experiences involve personally completing a desired task or a task similar to the desired task. When one feels successful, one also feels capable of engaging in the behavior again. People also gain self-efficacy by examining their own physiological states—for instance, when one appraises physiological arousal as excitement, they feel accomplished. Finally, when important others (e.g., friends, instructors) give encouragement and positive feedback (i.e., verbal persuasion) people feel more personally efficacious. In the present research, we focus specifically on mastery experiences as a source of efficacy.

Past research links self-efficacy to numerous health outcomes, such as levels of physical activity (Warner et al., 2014), recovery from illness (Robinson-Smith and Pizzi, 2003), and dietary quality (Cha et al., 2014). Self-efficacy is also a key factor in promoting health behavior change (Sheeran et al., 2016). According to past theory, self-efficacy can be domain-specific, such that it is influenced by the context of the specific goals that one wants to accomplish (Bandura, 1977). One of the domain-specific types of self-efficacy is coping self-efficacy.

Coping self-efficacy

In contrast to general self-efficacy, coping self-efficacy refers to one’s judgment about their ability to cope effectively with life challenges (Chesney et al., 2006). Put another way, coping self-efficacy is the feeling that one can effectively cope with a stressor (e.g., bad news). Some past research distinguishes between three types of coping self-efficacy: problem-focused coping, emotion-focused coping, and receiving support from close others (Chesney et al., 2006). Problem-focused coping involves efforts to overcome problematic aspects of stressful events. Emotion-focused coping involves efforts to manage emotional responses to stressful events. Receiving support from close others refers to seeking social support during stressful events, such as confiding in a friend or asking one’s family for help. In the present study, we do not delve into these facets, specifically, but instead focus on a generalized feeling that one can cope—regardless of the source of that ability—as an initial test of the relationship between coping self-efficacy and information avoidance.

Past research also distinguishes between adaptive and maladaptive coping strategies. Generally, there are adaptive problem- and emotion-focused coping strategies. Problem-focused strategies are aimed at eliminating the stressor with which one is coping. These can include things like searching for additional information on possible ways to eliminate the stressor (Ransom et al., 2005) or devising a plan to address a forthcoming stressor (Ryan, 2013). Emotion-focused strategies are aimed at addressing the emotions associated with the stressor. Adaptive strategies for emotion-focused coping include expressing one’s emotions through journal-writing (Baikie and Wilhelm, 2005) or practicing forgiveness toward others (Worthington and Scherer, 2004). In contrast, maladaptive strategies exacerbate the stressor or introduce additional stress. For instance, in the face of stress some people engage in binge eating (Sulkowski et al., 2011), using drugs to manage negative emotions (Staiger et al., 2009), or attempting to control uncontrollable stressors (Strentz and Auerbach, 1988).

Coping self-efficacy and adaptive coping are associated with a myriad of positive health outcomes including increased mental quality of life and decreased depression and psychological distress (Benka et al., 2014; Mikula et al., 2014; Rodkjaer et al., 2014). Similarly, general self-efficacy is widely implicated in health behavior change such as smoking cessation and engaging in physical activity (O’Leary, 1985). Although general self-efficacy is important to health more broadly, we predict that coping self-efficacy plays a unique role in health information avoidance. Specifically, when a person is faced with potentially threatening health information, having a sense that they can cope with the information is likely more helpful than having a sense that they can achieve goals. Nevertheless, no studies to date have examined the relationship between coping self-efficacy, general self-efficacy, and health information avoidance.

Thus far, perhaps the most relevant literature is that of the extended parallel processing model, which theorizes that responses to threatening information depend on self-efficacy (Witte, 1992). Specifically, when people perceive high levels of threat but low self-efficacy for responding to the threat, they may engage in defensive processes, like avoiding information (Witte, 1992). If, as we expect, increasing coping self-efficacy can reduce avoidance, it is important to understand how we might intervene to increase coping self-efficacy. The primary literature on improving self-efficacy is not in the domain of coping but is instead typically focused on general self-efficacy. One way to increase general and domain-specific self-efficacy is through mastery experiences. For example, group education sessions that provided both information about how to live a healthy lifestyle as well as opportunities to model and practice exercise techniques, resulted in improved exercise efficacy and subsequent increases in physical activity among cancer survivors (James et al., 2015). Moreover, women who attended education classes that offered opportunities to perform breast examinations using silicone models reported increased knowledge of breast cancer as well as efficacy for performing self-examinations (Yi and Park, 2012).

Most self-efficacy intervention research that incorporates mastery experiences has attempted to increase self-efficacy for behaviors (e.g., physical activity, self-examinations). Given that mastery experiences of physical activity and breast self-examinations were successful in promoting efficacy in those domains, we expected that considering mastery experiences of coping—here, specifically focusing on past coping successes—would increase coping self-efficacy and, in turn, reduce health information avoidance.

Objective

Given that health information avoidance can have long-term negative implications for health and well-being (e.g., Herman et al., 2015), it is important to understand the factors that may play a role in this behavior. Although traditionally, one might expect that coping self-efficacy is related to health information avoidance, no studies have tested this relationship experimentally. Our aim in the present work is to investigate whether coping self-efficacy influences health information avoidance and to contribute a potential method for reducing health information avoidance to the literature. The present work is guided by two primary research questions:

(1) Is health information avoidance associated with coping self-efficacy? If so, is this effect driven by a general sense of self-efficacy or a sense that one can cope with learning information about their health?

(2) Will a manipulation in which one focuses on their mastery experiences with coping be effective in reducing health information avoidance?

To answer question 1, Study 1 examined the correlation between health information avoidance and individual differences in general and coping self-efficacy. We expected that people would avoid health feedback less frequently to the extent that they had higher coping self-efficacy. After establishing a correlational link between coping self-efficacy and health information avoidance, Study 2 addressed question 2 by testing whether a manipulation to increase coping self-efficacy would reduce avoidance of type 2 diabetes feedback. In Study 2, we predicted that focusing on personal mastery experiences of coping would reduce avoidance of health information.

Study 1

We first wanted to examine whether coping self-efficacy related to health information avoidance. We expected that higher coping self-efficacy would relate to a lower likelihood of avoiding health information. We also wanted to ensure that feelings of general control/self-efficacy, do not underlie the hypothesized relationship, but that the relationship specifically stems from feeling like one can effectively cope. As such, we also examined the relationship between general self-efficacy and health information avoidance.

Study 1: Design

Participants and procedure

Data were collected as part of a study investigating threat, resources, and information avoidance (Howell, 2015). For the purpose of this paper, we focus only on the data relevant to coping self-efficacy, general self-efficacy, and avoidance. No report on the data has examined any of the self-efficacy variables. All study procedures were approved by the university’s Institutional Review Board.

Participants were 107 undergraduates (66 women, 41 men; M_age = 18.74 years old, SD_age = 1.78) participating for partial fulfillment of a research participation requirement. Experimenters dressed in medical scrubs greeted participants and told them the study was examining a disease known as thioamine acetylase (TAA) deficiency (Jemmott et al., 1986). In reality, the disease was fictitious, creating an environment where participants did not know their disease risk or have any background in the disease prior to participating. After providing informed written consent to participate, participants were stationed at a computer where they watched an informational video about TAA deficiency and its prevalence among college students. Then they completed an ostensible online risk calculator which they learned could calculate their lifetime risk for TAA deficiency. Afterward, participants completed measures in an online survey for coping self-efficacy and general self-efficacy and received an opportunity to learn their risk for TAA deficiency. Specifically, participants saw a question on the computer screen asking if they would like to learn their results from the online risk calculator, in which they could indicate “yes, please give me my risk estimate for TAA deficiency” or “no, I do not want to know my risk estimate for TAA deficiency.” At the end of the study, researchers fully debriefed participants. None of the participants suspected that TAA deficiency was a fictitious disease.

Measures

Coping self-efficacy

We assessed coping self-efficacy with four items (Howell, 2015) measuring participants’ confidence in their ability to cope with learning that they tested at high risk for a disease (α = 0.75). Participants indicated their agreement with items such as “I feel confident I could handle learning that I have TAA deficiency” and “I have people I can turn to if I learn that I have TAA deficiency” on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree).

General self-efficacy

We assessed general self-efficacy with the General Self-Efficacy Scale (Schwarzer and Jerusalem, 2010). The scale consists of 10 items assessing participants’ confidence in their ability to achieve desired outcomes (α = 0.93). Participants indicated their agreement with items such as “I can solve most problems if I invest the necessary effort” and “It is easy for me to stick to my aims and accomplish my goals” on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Health information avoidance

We assessed health information avoidance by asking participants whether they wanted to learn their risk for TAA deficiency based on the risk calculator. Participants selected from one of two options on the computer screen: “yes, please give me my risk estimate for TAA deficiency” or “no, I do not want to know my risk estimate for TAA deficiency.” The option to learn risk results was pre-selected, so that participants who decided to avoid viewing their risk results had to do so intentionally by selecting the option to avoid.

Analysis

All data management and analyses for these studies were conducted using R Studio version 3.4.1. First, we examined the bivariate associations between the predictor variables (general self-efficacy and coping self-efficacy) and the dichotomous outcome variable (avoidance of risk assessment). Next, we used a logistic regression analysis to examine the unique associations between the predictor variables and the dichotomous outcome variable (avoidance of risk assessment).

Study 1: Results

Results of all analyses are presented in Table 1. Overall, 20.6% of participants avoided learning their risk for TAA deficiency. In line with our hypothesis, coping self-efficacy was related to avoidance, r_pb(107) = −0.24, p = 0.02, CI_95% = [−0.41, −0.05], but general self-efficacy was not r_pb(107) = −0.06, p = 0.53, CI_95% = [−0.25, 0.13]. Also in line with our hypothesis, participants who reported greater coping self-efficacy were less likely to avoid their risk for TAA deficiency, OR = 0.58, X² = 5.22, p = 0.02, CI_95% = [0.36, 0.91]. General self-efficacy was not significantly related to avoidance, OR = 1.14, X² = 0.35, p = 0.55, CI_95% = [0.64, 2.10].

Table 1.

Results from logistic regression and point biserial association tests examining associations between self-efficacy and avoidance.

Health information avoidance	Coping self-efficacy			General self-efficacy
Health information avoidance	r_pb	r_pb [CI_95%]	p	r_pb	r_pb [CI_95%]	p
	−0.24	[−0.41, −0.05]	0.02	−0.06	[−0.25, 0.13]	0.53
	OR	OR [CI_95%]	p	OR	OR [CI_95%]	p
	0.58	[0.36, 0.91]	0.02	1.14	[0.64, 2.10]	0.55

Study 1: Discussion

In line with our hypotheses, Study 1 suggested that having a greater sense that one can cope with learning that one is at high risk for disease is associated with a lower likelihood of avoiding disease risk feedback. By contrast, general self-efficacy was not significantly related to avoidance, suggesting that the effect of coping self-efficacy was not driven by a general sense of efficacy, but is instead specifically about one’s coping ability.

Study 2

Study 1 suggested that coping self-efficacy was associated with health information avoidance. Of course, this correlation does not implicate coping self-efficacy as causal in information avoidance. As such, in Study 2, we aimed to manipulate coping self-efficacy and examine the effect on health information avoidance. Guided by self-efficacy theory (Bandura, 1993), we designed a manipulation in which participants considered a mastery experience—specifically focusing on one’s past coping successes—as a source of coping self-efficacy. Namely, we drew from past literature on adaptive and maladaptive coping strategies (Baikie and Wilhelm, 2005; Ransom et al., 2005; Staiger et al., 2009), to design two coping ability assessments in which participants reflected on their past problem-focused coping, emotion-focused coping, and social support strategies. We predicted that participants who considered their own coping successes would avoid their risk assessment for type 2 diabetes less frequently than would those who considered their coping failures or did not consider their coping ability. We also examined the role of considering one’s past coping failures and predicted that participants who considered their own coping failures would show increased information avoidance.

Study 2: Design

Participants and procedure

Participants were 326 undergraduates (244 women, 81 men, 1 unreported; M_age = 19.57 years old, SD_age = 2.15) who participated for partial fulfillment of research participation requirements. Procedures were similar to those of Study 1: experimenters dressed in medical scrubs greeted participants and told them the study was investigating prevalence of type 2 diabetes among college students. After providing written informed consent to participate, participants were stationed at a computer where they watched an informational video about type 2 diabetes and responded to an actual online diabetes risk calculator (adapted from http://www.yourdiseaserisk.wustl.edu) that produces comparative risk estimates based on responses.

Participants were then randomly assigned to either a high coping self-efficacy, low coping self-efficacy, or control condition. Participants in the two coping self-efficacy conditions were directed to an online assessment that ostensibly assessed their coping ability. Participants in the high coping self-efficacy condition received an assessment containing a list of common adaptive coping strategies (e.g., “Seeking advice from friends or family” and “Coming up with a plan to solve the problem”). Participants in the low coping self-efficacy condition received a similar assessment containing a list of common maladaptive coping strategies (e.g., “Avoiding friends or family” and “Ignoring the problem”). We developed the list of strategies with a group of 20 pilot participants in our research lab. Through an iterative development process, we created items that were both frequently endorsed and that people rated as “good” and “effective” coping strategies for the high coping self-efficacy assessment. Similarly, we created items that were both frequently endorsed and that people rated as “bad” and “ineffective” coping strategies for the low coping self-efficacy assessment. A full list of the items appears online at https://osf.io/kthxc/. In both conditions, we instructed participants to indicate which coping strategies they have engaged in during stressful events in the past, by clicking the boxes next to each strategy on the list. Participants could select multiple strategies and were supposed to intuit their own coping failures or successes. Based on pilot testing, we expected that participants would perceive themselves as good at coping in the high coping self-efficacy condition and bad at coping in the low coping self-efficacy condition. Participants in the control condition did not complete any assessment of their coping strategies.

Next, we presented participants with the opportunity to learn their risk for type 2 diabetes. Participants saw a single question on the computer screen asking them if they would like to see their results from the online risk calculator at the end of the study, in which they could answer “yes, please give me my risk for diabetes” or “no, I do not want to learn my risk for diabetes.” Pilot work in the same setting suggested that participants did not feel that the results of the risk calculator alone were consequential for their lives, and therefore were unlikely to opt out from viewing their risk results. As such, we modified the study slightly to make the results have a very small bearing on participants lives after the study: we told all participants that receiving a high-risk assessment from the online risk calculator would require attendance to a simple 15-minute consultation at the university health center sometime in the 2 weeks following the study. We chose this model based on the typical “follow up” that one might be subject to after a high-risk diagnosis at a physician’s office. Participants did not actually have to attend the appointment and learned so during debriefing procedures. Those who opted to view their risk assessment for type 2 diabetes were, however, given their actual comparative risk results from the online risk calculator. Finally, participants were debriefed and thanked for their time. All study procedures were approved by the university’s Institutional Review Board.

Measures

Information avoidance

We measured information avoidance by asking participants whether they wanted to learn their comparative type 2 diabetes risk; they selected from one of two options on the computer screen: “yes, please give me my risk for diabetes” (learning) or “no, I do not want to learn my risk for diabetes” (avoiding). The option to learn risk results was pre-selected, so that participants who decided to avoid viewing their risk results had to do so intentionally by selecting the option to avoid.

Analysis

We conducted three chi-squared tests to examine whether avoidance differed as a function of condition—specifically whether the participants in the high coping self-efficacy condition avoided their risk less frequently than did those in control condition and whether those in the low coping self-efficacy condition avoided their risk more frequently than did those in the control condition.

Study 2: Results

Results from all analyses are presented in Table 2. Overall, 44.8% of participants chose to avoid learning their diabetes risk.¹ As expected, participants in the high coping self-efficacy condition avoided their diabetes risk feedback significantly less often (38.4%) than did those in the control condition (55.0%), X²(1, 212) = 5.86; p = 0.02; φ = 0.17, CI_95% = [0.04, 0.30]. Contrary to our hypotheses, participants in the low coping self-efficacy condition (42.1%) actually avoided their diabetes risk less frequently than did those in the control condition, though the effect did not meet the traditional cutoff for statistical significance, X²(1, 214) = 3.55; p = 0.06; φ = 0.13, CI_95% = [−0.26, 0.004]. Additionally, avoidance rates did not differ between the low and high coping self-efficacy conditions, X²(1, 226) = 0.32; p = 0.57; φ = −0.04, CI_95% = [−0.19, 0.11].

Table 2.

Results from chi-square tests examining differences in percentage of avoidance by condition.

	Avoidance, n (% within condition)		X ²	φ	φ [CI_95%]	p
High efficacy versus control	High efficacy	Control	5.86	0.17	[0.04, 0.30]	0.02
High efficacy versus control	43 (38.4%)	55 (55.0%)
Low efficacy versus control	Low efficacy	Control	3.55	0.13	[−0.26, 0.004]	0.06
Low efficacy versus control	48 (42.1%)	55 (55.0%)
High efficacy versus low efficacy	High efficacy	Low efficacy	0.32	−0.04	[−0.19, 0.11]	0.57
High efficacy versus low efficacy	43 (38.4%)	48 (42.1%)

General discussion

We conducted two studies to investigate whether coping self-efficacy influences health information avoidance. In Study 1, coping self-efficacy, but not general self-efficacy was related to avoidance of risk for a novel disease. In Study 2, we examined the relationship between coping self-efficacy and information avoidance experimentally. Based on evidence from the general self-efficacy literature that mastery experiences can increase self-efficacy (James et al., 2015; Yi and Park, 2012), we directed participants to consider their past use of positive coping strategies (high coping self-efficacy condition) or negative coping strategies (low coping self-efficacy condition), or simply allowed participants to move forward with the study (control condition). We then examined whether participants would avoid learning their risk for type 2 diabetes. Consistent with our hypotheses, those who considered their past positive coping strategies were less likely than were those in the control condition to avoid learning their risk for diabetes.

We observed one unexpected result in Study 2. Contrary to our hypotheses, those participants who reflected on their negative coping strategies did not avoid learning information more than did those in the control condition. In fact, the effect of the low coping self-efficacy manipulation was in the same direction as that of the high coping self-efficacy manipulation. We think this unexpected finding may implicate one of three processes. First, it is possible that participants in the low coping self-efficacy condition automatically considered positive coping strategies and past successes when they completed the coping assessment. For instance, when someone considered how they had engaged in social withdrawal in response to a problem in the past, they might have also mentally contrasted that with ways they had sought social support in the past: Thinking about how they ignored their mother when they were dealing with a bad grade might also cause them to remember when they turned to their mother after a bad breakup. Second, it is possible that the coping ability assessments may have operationalized type of coping self-efficacy as opposed to coping self-efficacy itself. Thus, participants in the low coping self-efficacy condition may have perceived that having negative coping strategies is better than not having any coping strategies at all. Third, it is possible that participants in the low coping self-efficacy condition felt compelled to learn their risk in order to reduce the psychological discomfort caused by reflecting on their past failures to cope with stress. This latter hypothesis is in line with the literature on cognitive dissonance, which suggests that reflecting on past failures can prompt people to compensate by attempting to succeed in ways they failed before (Harmon-Jones et al., 2003). Thus, participants in the low coping self-efficacy condition may have made the decision to view their risk for type 2 diabetes as a way to affirm their coping abilities after being presented with information indicating that they were bad at coping.

Theoretical implications

The findings from our studies contribute to both the information avoidance and self-efficacy literatures. Although past theorizing on information avoidance assumes that people avoid information when they think they will be unable to cope with threats to their cognition, behavior, and affect resulting from learning bad news (Shepperd and Howell, 2015), we are unaware of any study that has examined the causal relationship between coping self-efficacy and information avoidance. Thus, the current research represents a promising initial step toward understanding whether prior theorizing about coping and information avoidance is accurate.

Our studies also advance the coping self-efficacy literature, which is primarily correlational in nature, in part because few studies have attempted to manipulate coping self-efficacy. Although several interventions to improve other types of self-efficacy exist in the broader self-efficacy literature (e.g., Yi and Park, 2012), few have targeted coping self-efficacy specifically. As such, the coping self-efficacy assessments from Study 2 may serve as an initial starting point for developing coping self-efficacy manipulations. Nevertheless, given the mixed findings of Study 2, further research is needed to establish an intervention.

Our studies also contribute to the coping self-efficacy literature by differentiating between general self-efficacy and coping self-efficacy, at least in the domain of health information avoidance. Namely, the results from Study 1 suggest that information avoidance is, in fact, driven by a sense that one can effectively cope, and not a general sense of control or belief that one can accomplish goals. Thus far, the most relevant literature in this area is that of the extended parallel processing model, which theorizes that people may avoid information when they perceive high threat but low self-efficacy (Witte, 1992). Our work extends this model by introducing the concept of coping with information and the potential role of coping self-efficacy in predicting health message processing and outcomes.

Practical implications

From an applied perspective, reducing health information avoidance may be key to promoting much-needed early detection of disease and promoting long-term health (Sweeny et al., 2010). The present study offers one possible psychosocial factor to target to reduce health information avoidance: coping self-efficacy. Our results suggest that encouraging people to reflect on past successes with coping can reduce health information avoidance. Although the manipulation occurred in a lab, we believe that it is easy to translate to applied settings. For instance, before physicians make recommendations for screening, they could address any patient concerns about coping with bad news about their health and help them focus on past coping successes to promote coping self-efficacy. Prompting people to focus on their own coping ability might be a simple and cost-free way to discourage health information avoidance.

Aside from healthcare settings, the findings from the current studies suggest that online health resources should consider employing methods to improve coping self-efficacy prior to presenting health information in order to increase the effectiveness of that information. Namely, having users focus on mastery experiences of coping may be a worthwhile strategy for increasing the usage of such information.

With the advent of technology, health information is becoming increasingly accessible (Murray et al., 2003). Past research in health informatics, or the study of health information delivered through technology (Yan et al., 2016), suggests that usage and acceptance of online health information depends on numerous factors like the credibility and perceived utility of the information as well as how the information is presented (Shin and Biocca, 2017; Shin et al., 2017). It is possible that perceived coping self-efficacy might influence the extent to which people receive these messages at all. As such, future research can examine the potential role of coping self-efficacy in avoidance and acceptance of online health information.

Limitations and future directions

The present findings are limited in a few notable ways that suggest important future directions for research. First, although participants in the high coping self-efficacy condition avoided their diabetes risk less frequently than did those in the control condition, they focused on past mastery experiences with coping as opposed to having novel mastery experiences with coping. This may explain why the effect size of our manipulation which, although significant, was somewhat small. It is possible that the effect of the manipulation would have been stronger if participants had in-the-moment experiences of mastery, especially in managing negative health news, before deciding to view their risk assessment. Future studies can provide mastery experiences with coping such as having participants write about a current stressor that they are coping well with or having participants devise a plan for how they would successfully cope with a high-risk result.

Second, future research can attempt to generalize the present results to other diseases and populations. From the population standpoint, our sample represents an important target for disease risk feedback: risk detection during emerging adulthood can be key to creating sustainable and effective behavioral change to reduce disease risk (Harris and Eastman, 2000). Nevertheless, further research expanding on this initial work to focus on older populations and those at higher immediate risk for disease is warranted. Although these studies bear replication in different diagnostic contexts and with other populations, they provide important initial insight into disease risk feedback avoidance.

Another important future direction is to investigate the causal role of specific facets of coping self-efficacy. Some research on coping self-efficacy suggests that it is a multi-dimensional construct, consisting of one’s perceived ability to respond to stressors by engaging in problem-focused coping, stopping unpleasant thoughts and emotions, and receiving support from friends and family (Chesney et al., 2006). In our studies, we tapped a broader form of coping self-efficacy—the general sense that one could cope—rather than any specific dimension of the construct. It is possible that interventions will be strongest if they address the sub-components of coping self-efficacy, rather than just attempting to influence people’s perceptions of their coping generally. As such, future research can more directly aim to modify various subcomponents of coping self-efficacy, and therefore to test the causal role of each in information avoidance.

Conclusion

Given that early detection and diagnosis are critical to improving long-term health outcomes, it is important to understand what might undermine people’s willingness to learn their risk for disease. Here we test one possible impediment: a lack of coping self-efficacy. We did so in two highly ecologically valid contexts where participants were greeted by experimenters in medical scrubs, completed a disease risk calculator, and faced a decision to view their risk assessment in what felt like a medical context. Collectively these two studies, one correlational and one experimental, suggested that greater coping self-efficacy relates to a reduced likelihood of health information avoidance. These findings expand the coping self-efficacy literature by providing a needed manipulation and offer a promising direction for interventions to stem health information avoidance.

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Study2_Analyses_Script for Coping self-efficacy influences health information avoidance by Jacqueline Hua and Jennifer L. Howell in Journal of Health Psychology

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Study2_Codebook – Coping self-efficacy influences health information avoidance

Study2_Codebook for Coping self-efficacy influences health information avoidance by Jacqueline Hua and Jennifer L. Howell in Journal of Health Psychology

Supplemental Material

Study2_Data – Coping self-efficacy influences health information avoidance

Study2_Data for Coping self-efficacy influences health information avoidance by Jacqueline Hua and Jennifer L. Howell in Journal of Health Psychology

Footnotes

Data sharing statement

A complete set of de-identified data and analysis scripts are available at .

Declaration of conflicting interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jacqueline Hua

Notes

References

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