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Advice: Communicating to Support and Influence

Summary and Keywords

Advice is a recommendation for action that includes both suggestions for behavior and ways of feeling and thinking about the problem. It is a ubiquitous phenomenon in personal and professional settings, and functions as a form of both social support and social influence. Advice often improves coping and decision-making outcomes but can also be perceived as intrusive, threaten recipient’s sense of competence and autonomy, and damage relationships.

Although advisors often have expertise that can benefit the recipient, advice recipients often discount and underutilize advice, to their disadvantage. Recipients are more likely to utilize advice from advisors they trust, who engender confidence, and who have more expertise or experience. They are also more likely to seek and use it when they have not thought of solutions independently. Recipients who are overconfident, have more expertise, or have more power than an advisor are much less likely to seek and utilize advice. When giving advice, advisors often consider different factors than they would if they were making decisions for themselves, resulting in advice that is more normative and less tailored to individual preferences.

Advice can be delivered in a variety of ways, and this stylistic variation has consequences for recipient outcomes. For example, highly direct or blunt forms of advice underscore the advisor’s implicit claim to status and often generate more negative evaluations of the advice and advisor. Advice message content also influences recipients’ advice evaluation. Content that emphasizes efficacy of the action, feasibility, and limitations of the advice tends to improve evaluation and utilization of advice. This research is synthesized in advice response theory (ART), which indicates that advice outcomes are influenced by message content and style, interaction qualities, advisor characteristics, recipient traits, and features of the situation for which or in which advice is sought. Behaviors that co-occur with advice, such as argumentation, emotional support, and planning, also influence outcomes. The sequencing of advice in interaction also matters; the integrated model of advice (IMA) indicates that advice in supportive interactions is best placed after emotional support and problem analysis.

The contexts in which advice are given influence the exchange and outcomes of advice. These include personal and professional relationships, in which relational cognitions and professional norms affect the process and outcomes of advising; groups and organizations, in which advising processes become complex due to the multiplicity of relationships, goals, and expectations; cultures, in which advice-seeking and advice-giving varies in perceived appropriateness; and digital environments, which are often valued for advice that is unobtainable elsewhere.

Keywords: advice, advising, social influence, social support, informational support, persuasion, decision making

Definition and Function

Advice is a recommendation for action in response to a problem (MacGeorge, Feng, & Thompson, 2008), where actions include both overt behaviors and ways of feeling and thinking (MacGeorge & Hall, 2014), and problems may encompass the range from intellective decision-making tasks (choosing a correct answer; Van Swol, 2011) to significant personal stressors (Seiders, Flynn, Berry, & Haws, 2015). Notably, although people do obtain recommendations for action from texts and media created for large audiences (e.g., FAQ lists, advice columns, “self-help” books), the focus herein is advice as an interpersonal phenomenon, in which recommendations for action are made from single individuals to specific others. Because it is commonplace for people to experience problems and others to be involved in responding to those problems, advice is a ubiquitous phenomenon. People exchange advice in contexts both personal (Carlson, 2014; MacGeorge & Hall, 2014) and professional (Battistoni & Colladon, 2014; Labrie & Schulz, 2014), in relationships that vary in intimacy and power relations (Feng & Magen, 2016; Son & Kim, 2013), in interactions conducted both face-to-face and via communication technologies (MacGeorge, Guntzviller, Branch, & Yakova, 2016; Talboom & Pierson, 2014), and in diverse cultures.

Communication scholars have described advice as having two primary functions: social support and social influence (MacGeorge, Feng, Butler, & Budarz, 2004; Wilson & Kunkel, 2000). Expanding on this framework, MacGeorge and Van Swol (2018a) identify prototypical characteristics that distinguish advice from other forms of social influence and social support, including advice being made exigent by a problem, intended to guide future action and to be helpful, and delivered one-to-one by an advisor who has or claims greater expertise than the recipient. For advisors, advice may be offered to assist others with their problems, and indeed is sometimes regarded as a specific type of informational support (a category that usually includes information and opinion; Bonaccio & Dalal, 2006). However, giving advice is also a means of guiding others’ behavior and is identified as a common type of interpersonal influence goal (Dillard & Knobloch, 2011; Dillard & Wilson, 2014). For recipients, advice can produce supportive outcomes that include improved coping and reduced distress, and it may persuade them to undertake particular means of resolving their problems. Indeed, research repeatedly demonstrates that advice improves decision making. For example, on intellective tasks utilizing advice leads to greater accuracy than privileging one’s own perspective, even when given by peer advisors who have no superior expertise (Gino & Schweitzer, 2008; Yaniv, 2004). Because advice can support and persuade, it has (at least) two additional functions: creating and sustaining connections between advisors and advisees in advising relationships and networks (Battistoni & Colladon, 2014; Creswick & Westbrook, 2010), and thereby generating social capital that can be accessed by people who have developed those connections (Lomi, Lusher, Pattison, & Robins, 2013; Zhang, Zheng, & Wei, 2009).

This functional analysis of advice does not indicate that these functions are uniformly achieved—or even intended. Recipients of advice are not uniformly persuaded by it, and often underutilize or ignore it, even to their own detriment (Yaniv, 2004; Yaniv & Choshen-Hillel, 2012a). Advice may not only fail to be perceived as supportive, but can damage identity and relationships (Goldsmith, 2004; Goldsmith & Fitch, 1997). Moreover, not all advice is provided with strong supportive or persuasive intention: advisors may give advice for other reasons, such as building social status for themselves (Lomi et al., 2013), or avoiding more tangible support. Further, what advisors intend may not align with recipients’ perceptions or outcomes (Danziger, Montal, & Barkan, 2012); indeed, advisors and advice recipients need not even agree on whether advice was given or intended to be given (MacGeorge, Guntzviller, Branch, & Yakova, 2015). Still, to the extent that advice fails to achieve social support or social influence goals, its function to enhance social connections and capital likely also declines.

Advisors and Advice Recipients

The roles of advice recipient (or advisee) and advisor are distinctive; in general, the problem and any subsequent action to resolve it belong to the former, whereas the latter claims expertise with regard to the solution. Correspondingly, recipient and advisor perspectives can diverge in ways that significantly impact advice outcomes. One of the most consistent findings in research on advice is that people often do not accept or fully utilize the recommendations they receive. Instead, advice recipients tend to engage in egocentric discounting, assigning more weight to their own ideas than their advisors’ when making decisions (Yaniv & Kleinberger, 2000). This is unfortunate, given that advisors often have different perspectives than decision makers, such that using advisor input as a corrective to personal perspective can be highly advantageous (Minson, Liberman, & Ross, 2011).

Given the negative consequences for not using advice, considerable research has examined factors influencing why people do or do not seek or utilize advice. There are several characteristics of the advisor that consistently influence advice utilization, including confidence, expertise, trustworthiness, and perceived motivations. Decision makers are more likely to use advice from more confident advisors (Sniezek & Buckley, 1995; Sniezek & Van Swol, 2001). Indeed, advice recipients often use confidence as a heuristic for determining advisor accuracy and expertise (Price & Stone, 2004) even though the relationship between confidence and accuracy is not always strong, and advisors often exhibit overconfidence (Erev, Wallsten, & Budescu, 1994). In addition, when judgments of expertise can be made, decision makers are more likely to use advice from advisors with more expertise and experience with the problem domain (Feng & MacGeorge, 2006; Harvey & Fischer, 1997; Yaniv & Kleinberger, 2000)

For advice recipients, there is always a degree of uncertainty about the motives and competence of the advisor. Therefore, advisor trustworthiness is important in overcoming that uncertainty to utilize advice (Sniezek & Van Swol, 2001). The determinants of trust differ by the type of task the decision maker is facing. On more intellective tasks with a demonstrably correct answer, like calculating a math problem, decision makers are more likely to develop trust from the confidence and expertise of the advisor. However, on tasks where is it difficult to demonstrate the superiority of one option over another and decisions are more a matter of taste and values, decision makers trust advisors who share similar values as themselves (Van Swol, 2011). Decision makers are also sensitive to whether an advisor shares the same incentives and motivations as themselves. For example, an advisor may have motives to benefit financially from the advising interaction and is less concerned with the long-term quality of the decision made. When advisor’s and decision maker’s motivations and goals align, the decision maker will be more likely to trust the advisor and utilize advice (Tan & Lee, 2015).

Characteristics of the recipient also affect whether advice is used—or solicited in the first place. People who are overconfident overestimate the extent to which they are correct or their ability to competently solve a problem (Moore & Healy, 2008), and as a result, often fail to seek advice because they perceive no need for it (Sniezek & Buckley, 1995). If given advice, highly confident advisees will be less likely to use it (Gino & Moore, 2007; Soll & Larrick, 2009). In addition to confidence, having expertise in the subject matter will reduce the extent to which a decision maker will seek and utilize advice (Yaniv, 2004). Power also reduces the solicitation and utilization of advice because powerful individuals often have more confidence and optimism in their decision making, which would preclude their perceived need for advice (See, Morrison, Rothman, & Soll, 2011). Further, advice may be especially face threatening to a more powerful individual because advice could imply a lack of competence, which could threaten a powerful person’s status in an organization (Burris, 2012). Advice recipients’ emotional states can also affect how receptive they are to advice, even when those emotions are unrelated to the advising interaction. Advice recipients who feel positive other-directed emotions (e.g., gratitude) or negative self-directed emotions (e.g., shame or anxiety) are more likely to utilize advice, whereas advice recipients who feel positive self-directed emotions (e.g., pride) or negative other-directed emotions (e.g., anger) are less likely to utilize advice (de Hooge, Verlegh, & Tzioti, 2013; Gino & Schweitzer, 2008).

The way advice is sought can affect the extent to which it is utilized. Advice recipients who receive advice before they have had an opportunity to think about solutions independently are more likely to utilize the advice. But this type of advice, called cued advice (Sniezek, Paese, & Switzer, 1990), often creates unwarranted confidence in the advised decision because recipients have not considered other alternatives. On the other hand, if an advice recipient considers alternative solutions before receiving the advice, advice that contradicts an already-considered solution is especially likely to be discounted. People have a confirmation bias and tend to seek information that supports an initial opinion. This is problematic because people are especially likely to improve their decision making and problem solving when they incorporate advice that is different from their own thinking (Minson et al., 2011).

Although there is less research on the advisor’s perspective, one consistent finding is that advisors often offer advice that is different from what they themselves would do. Advisors consider different factors when giving advice than what they would consider when making decisions for themselves. Advisors engage in less biased information research and are less subject to the confirmation bias than people making decisions for themselves (Jonas & Frey, 2003; Jonas, Schulz-Hardt, & Frey, 2005). People making decisions for themselves consider more information and are more likely to make choices reflecting individual preferences and uniqueness; however, when recommending choices for others, advisors focus on more salient information and dominant attributes and recommend options that are less unique and that more people would prefer (Kray, 2000; Kray & Gonzalez, 1999). In other words, when providing advice, advisors tend to think from the perspective of normative others, rather than trying to understand the advice recipient’s unique situation and weighting of different criteria. In addition, advisors are more likely to suggest more risk-taking options for others than they would consider when making decisions for themselves (Beisswanger, Stone, Hupp, & Allgaier, 2003). The tendency of advisors to recommend different options than they themselves would pick may be due to different levels of effort, information, familiarity, and motivation (Fischhoff, 1992; Kray & Gonzalez, 1999).

Ultimately, a lack of mutual understanding and perspective taking between an advisor and decision maker can reduce advice utilization. In general, advice recipients understand their own perspective on a problem and its potential solutions, but they lack corresponding insight into the advisor’s reasoning. Discussing the problem or decision with an advisor and trying to reach a consensual decision does increase utilization of advice, possibly because through reaching a consensual decision, decision makers gain a better understanding of advisors’ reasoning, and advisors gain a more nuanced understanding of the decision maker’s preferences and needs (Minson et al., 2011; Yaniv & Choshen-Hillel, 2012b).

Advice Messages

The way recipients respond to advice is influenced by several aspects of advice message content and style, where content refers to what is being advised and style refers to the language being used to present the content. Key aspects of content evaluation include the efficacy of the advised action (will it work?), its feasibility (can it be accomplished?), and its limitations (what drawbacks does it have)? Multiple studies demonstrate the influence of these evaluations on outcomes that include recipients’ perceptions of advice quality, reported facilitation of coping with the problem, and implementation of the advice or intention to implement it (Feng & MacGeorge, 2010; MacGeorge et al., 2004). Research also indicates that advice messages that include argumentation addressing these issues boost perceptions of advice quality (Feng & Burleson, 2008). Evaluations of advice are also influenced by confirmation, or whether the content is perceived to align with the recipient’s preexisting intentions. Recent work has expanded the focus on aspects of advising content to examine the effects of gain and loss framing, where gain framing refers to emphasizing the benefits of taking action, and loss framing refers to emphasizing the costs of not taking action (Jang & Feng, 2017). Gain-framed advice messages produced higher evaluations of advice quality and higher perceptions of facilitation of coping than did loss-framed advice messages.

Much as advice content varies, the style of advice is also highly variable, and this variation affects advice outcomes. Advice takes a wide range of forms in discourse (Locher & Limberg, 2012). It is probably most easily recognized when presented in single-sentence, imperative form (“You should do X”), because a single recommendation for action is unambiguously asserted. Yet advice can be conveyed in declaratives (“It’s a good idea to . . .”) and interrogatives (“Why don’t you . . .?”), including inquiries about the appropriateness of a possible future action (“Would it work to . . .?”) rather than direct recommendation for doing it (Butler, Potter, Danby, Emmison, & Hepburn, 2010). Advice may also take still more indirect or “off-record” forms, such as when advisors describe their own prior experiences and actions (Goldsmith, 2004) or those of third parties. By giving advice, advisors implicitly claim epistemic status, or communicative rights with respect to the advice recipient, his or her problem, and how to resolve it (Heritage, 2012; Heritage & Lindstrom, 2012). Correspondingly, advisors can use language in ways that either underscore or downplay this status—such as giving advice indirectly or with indications of hesitancy to claim less status, versus giving it directly or emphatically to assert more status. Such linguistic formulations contribute to variation in the extent to which advice is observably polite, face saving, or mitigated, versus impolite, face threatening, or aggravated (Goldsmith & MacGeorge, 2000).

Indeed, advice has the potential to threaten recipients’ face or public image (Goldsmith, 2004), including perceptions of being independent, competent, or liked by others (Brown & Levinson, 1987; Lim & Bowers, 1991). When advice is perceived as more face threatening, it is evaluated less positively and less likely to be implemented (Goldsmith & MacGeorge, 2000; MacGeorge, Lichtman, & Pressey, 2002; MacGeorge, Smith, Caldes, & Hackman, 2017). Further, language that addresses face concerns can improve evaluations of advice, though these findings on specific types of language are inconsistent (Goldsmith & MacGeorge, 2000), probably because language choices that can convey concern for face can also convey other messages that may negatively influence recipients’ perceptions (e.g., polite language can convey lesser power or confidence).

Much of the influence of advice message content and style on advice outcomes has been synthesized within advice response theory (ART; see Feng & MacGeorge, 2010; MacGeorge, Guntzviller, Hanasono, & Feng, 2016). This theory provides a framework for organizing factors that influence how recipients evaluate and utilize advice. This theory suggests distinctions between message content and style, interaction qualities, advisor characteristics, recipient traits, and features of the situation for which or in which advice is sought. In addition to identifying efficacy, feasibility, limitations, confirmation, and politeness as key content and style influences on advice outcomes, ART describes message evaluations as the most proximal influences on recipients’ advice outcomes and positions advisors’ characteristics (e.g., expertise, trustworthiness) as more distal influences that influence outcomes by way of biasing message evaluations. Studies provide support for this contention, showing that advisor characteristics have only weak or nonexistent direct effects on outcomes when message evaluations are included (Feng & MacGeorge, 2010; MacGeorge, Guntzviller et al., 2016). ART also contends that message content and message style have differential influences on outcomes (Feng & MacGeorge, 2010; MacGeorge, Guntzviller et al., 2016) with content having stronger influence on persuasive outcomes of advice (e.g., likelihood of implementation) and politeness having stronger influence on socioemotional outcomes (e.g., facilitation of coping).

Advising Interactions

Although methods for studying advice have often focused on the isolated advice message (see discussion of the “message paradigm” in MacGeorge, Feng, & Guntzviller, 2016), naturally occurring advice is often delivered in an interaction, where the advice itself can stretch over multiple turns, or recur as advisors recommend multiple actions or the same action repeatedly. The extent of advice has implications for outcomes. In one study of interactions between friends, increased quantity of advice reduced perceived politeness of advice, which in turn influenced advice quality, advisor helpfulness, and conversational satisfaction. Further, repetitive advice appears associated with lower evaluations of advice quality from its recipients (MacGeorge, Guntzviller, Branch, et al., 2016).

Beyond the quantity of advice, behaviors that accompany advice have the potential to affect its interpretation and outcomes. One aspect of interactional sequence shown to affect advice outcomes is the extent to which advice is solicited. Regardless of whether they explicitly request advice, when recipients report greater receptiveness (i.e., desire to receive advice from an advisor) to advice, they evaluate it more positively (MacGeorge et al., 2004). In research examining what was said prior to the delivery of advice, advice that was not requested is less likely to be implemented (Deelstra et al., 2003; Smith & Goodnow, 1999), promotes greater face-threat and reactance (Fitzsimons & Lehmann, 2004; Goldsmith, 2000), and is less satisfying (Chentsova-Dutton, 2012). However, the degree of “unsolicitedness” also matters. In two studies that distinguished between advice that was “solicited” (requested), “guaranteed” (not requested, but given) and “imposed” (given despite expressed disinterest), there was little difference in the evaluation of solicited and guaranteed advice, except when the problem being advised upon was highly personal. Imposed advice, not surprisingly, received less positive evaluations than the other two types (Van Swol, MacGeorge, & Prahl, 2017).

In supportive interactions between relationship partners, advice evaluation appears to depend, at least in part, on the quality and sequence of other supportive behavior from the advisor. When advisors provide higher quality emotional support during interaction, the advice they give is also evaluated more positively (MacGeorge, Guntzviller, et al., 2017). Further, experimental studies (Feng, 2009, 2014) show that advice offered following emotional support and problem analysis messages is perceived as higher in quality, more facilitative of the recipient’s coping, and leading to stronger implementation intention than advice that does not follow this sequential pattern. These latter findings provide the foundation for the integrated model of advice (Feng, 2009), which proposes that emotional support and problem analysis prepare a distressed person for greater receptiveness to advice.

Perhaps not surprisingly, some advisee behavior which appears to signal how advice is being received, provoke certain kinds of responses from advisors, and ultimately contribute to more or less satisfying or effective interactions. Conversation analysts have identified a range of resistance strategies employed by advice recipients, such as describing obstacles toward carrying out the advised action, minimizing the importance of the action, claiming to have undertaken the action already, asserting their own knowledge and competence, identifying an agenda that is distinct from or contrary to the advisor’s, invoking other authorities against the advised action, and admitting to an irrational basis for resisting the advice (Shaw & Hepburn, 2013; Vehviläinen, 2009; Waring, 2005, 2007a; Ylänne & John, 2008). Recipients also respond to advice with minimal acknowledgment and efforts to change the topic (Heritage & Lindstrom, 2012), or with “complex acceptance” in which advice is acknowledged as useful, but recipients assert prior awareness of its utility, or claim reasons why the advised action has not yet been carried out (Waring, 2007a). Correspondingly, advisors utilize a variety of strategies that appear designed to preempt resistance, including polite or epistemically down-graded ways of delivering advice (Butler et al., 2010; Riccioni, Bongelli, & Zuckzkowski, 2014) and pre-accounts for recommending the advised action (Waring, 2007b). Once recipients have expressed resistance, advisor responses include expressing concern about the problem, asking questions, defending the advised action, giving alternative advice or information, and repeating or reformulating the advice (Hepburn & Potter, 2011; Heritage & Lindstrom, 2012; Pudlinski, 2012; Waring, 2007b).

Because advisors do not necessarily “give up” when recipients resist, extended conversational trajectories of advising and resistance may evolve (MacGeorge, Guntzviller, Branch, et al., 2016). At least four such trajectories appearing in interaction characterized by lower evaluations of advice quality: sustained resistance (in which the advisor alters the advice, but the recipient continues to resist), advisor persistence (in which the advisor persists in offering the same advice), irrational resistance (in which the recipient admits that the resistance to the advice is not warranted, but resists anyway), and contesting the problem (in which recipient and advisor disagree about the character of the problem and the corresponding appropriateness of advice).

Although little-studied to date, recipients’ own problem-solving behavior appears to have a complex relationship with advising outcomes. In a study of advising interactions between friends (MacGeorge et al., 2015), the quantity of advice recipients’ planning that occurred prior to the initial advice (controlling for total quantity) was negatively associated with advice quality, intention to implement, and advisor helpfulness even though neither quantity nor placement of planning behavior was associated with perceptions of advice content (e.g., efficacy) or politeness. These findings are consistent with the operation of egocentric bias (Yaniv, 2004). A greater quantity of expressed planning behavior prior to receiving advice demonstrates that recipients have a plan already in mind, against which any advised actions must compete. In addition, the verbal formulation of plans likely enhances commitment to those actions (Tormala & Petty, 2004), generating greater resistance to advice.

Advice in Personal and Professional Relationships

Personal Relationships

There is no question that advice is a key aspect of support provision and an expectation in personal relationships (Hall, 2012). Indeed, certain patterns of advice exchange are characteristic in particular types of personal relationships across the lifespan (MacGeorge & Hall, 2014). Parents, for example, segue from directing their children to advising them as they move from early childhood to early adolescence. Adolescents continue to take advice from parents, but begin to seek and rely more on peer and sibling advice, and may also be influenced by advice from other relatives (e.g., aunts and uncles). This pattern continues through “emerging adulthood,” during which romantic partners and spouses begin to assume primary advising roles. As adult children’s parents age, a certain amount of role reversal is common, such that adults move into advising roles with respect to their parents, but even elderly siblings often continue to advise one another. Studies also point to advising on particular topics as characteristic in certain kinds of personal relationships, such as siblings and friends with regard to adolescent sexuality (Adams & Williams, 2011) and grandmothers on parenting (Aubel, 2012).

Surprisingly, beyond who gives advice to whom (and to a limited extent, about what), much less is known about the influence of relationships on advising processes. It is true that communication scholars have typically studied advice as support that is provided in relationship contexts (e.g., friendships; Guntzviller, MacGeorge, & Brinker, 2017; MacGeorge, Guntzviller, Hanasono, et al., 2016), so theory on advice that emerges from communication scholarship (e.g., advice response theory, the integrated model of advice) is arguably theory about how advice is evaluated in these relational contexts. (By contrast, given the typical operationalizations of advice in most psychological or sociological research, theory developed therein is implicitly or explicitly about advising as it occurs in professional and other role relationships.) However, most research has not directly examined qualities or dimensions of relationships as influences on seeking, provision, or evaluation of advice (Branch & Dorrance Hall, 2018; MacGeorge, Feng, et al., 2016). Some previously discussed characteristics of advisors (e.g., power, expertise, trustworthiness) are arguably “relational” either to the extent that they are defined relative to the recipient, or assessed from the recipient’s perspective, but the conceptualization and operationalization of these variables tends to position them as characteristics of the advisor rather than the relationship between advisor and recipient.

Some 21st-century work has begun to take more seriously the ways in which relationship qualities affect the evaluation and outcomes of advice. Work on the evaluation of advice from parents indicates that emerging adults evaluate advice more positively to the extent that they perceive parents are more similar to themselves, and supportive of their autonomy (Carlson, 2014, 2016). Guntzviller et al. (2017) showed that perceptions of advice quality for both advisors and recipients were influenced by the quality of prior support provision. Branch and Dorrance Hall (2018) have called for expansion of this work into a greater focus on relationship cognitions, including attitudes, perceptions, attributions, and other aspects of thinking about relationships and relational partners. For example, advising behavior and evaluation in relationships is likely influenced by attachment style (Mikulincer & Shaver, 2007) and relational uncertainty (Solomon, Knobloch, Theiss, & McLaren, 2016).

Professional Relationships

Clearly, advising processes are situated within professional as well as personal relationships. Indeed, there are multiple professional roles to which advising is central (MacGeorge & Van Swol, 2018b), including educational roles (e.g., teachers, tutors, and academic advisors), health-care roles (e.g., doctors, dentists, therapists) and myriad business and organizational roles (e.g., supervisor, mentor, team member). In many respects, the profession of law is defined around the provision of legal advice (McGinniss, 2018). Research on advice in these professional relationships differs from research on advice in personal relationships insofar as there has been somewhat greater focus on understanding advising processes in order to improve communication as it occurs within particular types of relationships. Legal scholars, for example, have examined lawyer-client relationships and the way lawyers advise within those relationships (McGinniss, 2018). Similarly, because medical advice has such potential for positive impact on health, researchers have focused on qualities of physicians and interactions that lead to greater uptake of advice by patients (D’Angelo & D’Angelo, 2018). However, as with research on advice in personal relationships, there has been little advancement to date on theorizing how variation in characteristics or dimensions of professional relationships predict advice seeking, provision, evaluation, and outcomes across different specific relationships.

To illustrate, the power differential between advisor and advisee varies substantially across different professional relationships. For example, advice is exchanged both in co-worker or team member relationships in which neither party has more control over the other’s behavior outcomes and in supervisor-supervisee relationships where supervisory advice may function essentially as directive rather than suggestion. Research on power suggests certain kinds of effects, such as the tendency for the more powerful relational partner to discount advice from the less powerful partner (Tost, Gino, & Larrick, 2012) and even seek to punish less powerful individuals whose advice is seen as too critical (Tourish & Robson, 2006). However, such findings have yet to be integrated within a theory or model of advising in professional relationships such that the influence of power is modeled not only in laboratory experiments or within specific types of relationships but as a general influence on advising in professional relationships—and one that interacts with other factors that vary in these relationships.

Several such factors are suggested by looking across the scope of professional relationships in which advising occurs (MacGeorge & Van Swol, 2018b). Advising processes in professional relationships appear to be influenced by whether advice is principally to help the individual advisee (e.g., therapy, tutoring), principally in service of group or organizational goals (e.g., advice in workplace teams), or some combination of the two (e.g., mentoring); whether the content of the advice is principally about professional or personal concerns, which corresponds roughly to the distinction between advising on intellective tasks that have a correct or best answer and value tasks on which taste may vary widely; whether advisor and recipient are in the same group, in different groups but within the same larger organization, or are unconnected by professional (or social) structures; whether the advice is paid for, and whether the payment comes from the advisee or the advisee’s group or organization; and whether there are codes of conduct that prescribe who may advise whom, on what topics, or in what manner.

Advice in Groups and Organizations

Giving advice in groups and organizations is arguably more complicated than in dyads because issues such as social dynamics, status, and hierarchy are more salient and influence how advice is given and received. When advising groups, one may be an outsider offering advice to a group or one may be a member of the group and offering advice to fellow members while working on a shared problem or decision. When an outside advisor offers advice to a group or dyad, research has found that groups are more resistant to advice than individuals. Dyads are less likely to incorporate advice because the process of collaboration increases their confidence level, even though dyads are no better at judging the accuracy of advice than individuals (Minson & Mueller, 2012). Similarly, group discussion increases confidence but not accuracy (Heath & Gonzalez, 1995). Thus, although groups are often used to make decisions to increase diversity of perspectives and information, when a diverse opinion comes from an outside advisor, groups may actually be less likely to benefit from the advice than individuals.

When advising within groups, the tendency to downplay diverse information and opinions continues. Confirmation bias creates a tendency to discount advice inconsistent with initial opinions (Mojzisch, Kerschreiter, Faulmüller, Vogelgesang, & Schulz-Hardt, 2014), and within groups there is a further tendency to discount advice inconsistent with the majority opinion. Group members evaluate other group members who provide majority preference-consistent advice more positively and provide positive verbal and nonverbal feedback. These social dynamics then can amplify the focus on preference consistent advice and information because not only does the advising group member receive positive feedback, but other group members witness the feedback and have an incentive to focus and repeat that preference consistent advice (Mojzisch et al., 2014). As a result, any benefits of receiving advice from group members with minority opinions (Nemeth, 1986) is less likely to be realized because the social dynamics of the group favor preference consistent advice. In addition, groups have a tendency to focus on and discuss information known to all members before discussion (for reviews, see Lu, Yuan, & McLeod, 2012; Prahl, Dexter, Braun, & Van Swol, 2013). This known, shared information confirms what members already know: as a result, when a member mentions shared information they often receive positive feedback from others in the group, and other members in turn feel confirmation that information they know was mentioned. Hence, shared information can be mutually enhancing to all group members, which increases group members tendency to focus and repeat it (Wittenbaum, Hubbell, & Zuckerman, 1999). Like preference-consistent information, these social dynamics help amplify a group’s focus on shared information. As a result, advice from a group member that is new information other members have not heard before is likely to be discounted and ignored in the group. However, casting a group member in the assigned role of advisor or highlighting that group member’s expertise can mitigate this bias toward shared information and increase acceptance of advice with unshared information from that member (Stasser, Stewart, & Wittenbaum, 1995; Van Swol & Ludutsky, 2007). Group members’ discounting of advice containing new, unshared information mentioned by a fellow member is analogous to individual’s ego-centric discounting of advice and may be driven by similar processes, such as inability to understand the reasoning behind the new perspective.

Within organizations, there are several challenges to seeking and giving advice. One of the challenges is knowing who to ask or who needs advice. Given the distributed expertise of organizational members, it is not always easy to know who knows what. Research on transactive memory systems examines how expertise directories develop in organizations. Transactive memory systems are a form of group-level cognition in which people store knowledge and coordinate use of that knowledge to accomplish tasks (Hollingshead, 1998). The important component of transactive memory systems is the directory of knowledge so that members may access each other’s expertise when they need advice. Transactive memory systems can develop organically through interaction and experience, be assigned and made explicit through organizational roles, or be assumed through salient characteristics such as gender or ethnicity. Thus, transactive memory systems may develop easily in small interacting groups where members have experience with each other; but in larger organizations, there is often a need to create infrastructure, like a directory or organizational intranet, where members can search for each other’s expertise (Yuan, Fulk, & Monge, 2007). When organizational members have a shared understanding of the transactive memory system, then members know that others will hold them responsible for certain categories of information, and members can specialize in what type of information they remember and encode.

Generally, transactive memory systems increase organizational performance. Teams with well-developed systems work quicker and make higher-quality decisions. Further, when a person contributes advice in their recognized area of expertise, it is more influential (Hollingshead, 1998; Liang, Moreland, & Argote, 1995). However, like any specialization, transactive memory systems increase vulnerability if members with one area of specialization leave the organizations, creating gaps in who is curating certain knowledge. In addition, in large organizations members may have ulterior motives for hiding their knowledge, possibly to avoid being swamped by those seeking advice or to reap benefits from having exclusive access to information. Therefore, there may be incentives to not sharing information and advice and to hamper the development of transactive memory systems (Wittenbaum, Hollingshead, & Botero, 2004).

Transactive memory systems and networks of people from whom organizational members can seek advice can come from members inside the organization or outside (Alexiev, Jansen, Van den Bosch, & Volberda, 2010). Outside sources of advice can include consultants hired for their expertise and colleagues at other organizations in similar roles (McDonald & Westphal, 2003). Outside advice may be especially important for providing innovative and unbiased ideas. Advice from inside the organization may be more biased and confirming of initial ideas, but seeking advice from others within the organization can help create an open organizational culture in which members have a voice (Alexiev et al., 2010).

Finally, in order for advice to flourish within organizations, there needs to be an organizational culture in which advice is accepted and members feel enough psychological safety to provide advice, especially if the advice is critical of superior’s ideas. Giving and receiving advice can be a face-threatening act in and of itself, but in organizations with different levels of hierarchy, employees may be especially wary of giving advice to those with more status and power (Pittinsky & Poon, 2005).Yet, given the benefits of advice for organizational performance (Foster & Hoff Macan, 2002; Steinel, Abele, & De Dreu, 2007), creating an open atmosphere to provide advice should be an important goal for organizations.

Advice Online

In the course of just a few decades, exchanging support with others through digital means has gone from being highly unusual to completely mainstream, with hundreds of thousands of online venues specific to particular concerns (Wright, 2016) alongside the capacity to use general social media, e-mail, messaging systems, and video conferencing to seek and provide support. Support seekers can use online platforms to find support providers who may be more altruistic, accessible, and expert than local alternatives, especially if they are dealing with unusual or stigmatizing conditions. Correspondingly, they may receive a higher quantity and quality of support (Barak, Boniel-Nissim, & Suler, 2008). Research specific to online advice remains relatively sparse in comparison to research on online support more broadly, but a picture of advice online is gradually coming into focus (for a more detailed review, see Feng, Zhu, & Malloch, 2018).

Similar to face-to-face (FTF) supportive interaction, advice is central to online support exchanges. Online advice seeking is motivated by factors that include the perceived quality and quantity of offline support, the loneliness of the support seeker, and the virtual availability of online support providers (Feng et al., 2018). In online communities, advice giving is more likely to come from support providers who share the advice seeker’s problem or experience (Smithson et al., 2011). Advice givers online may be more responsive when support seekers’ appeals are more specific and more emotional (Ruble, 2011) and when responses given by others to the same support seekers are more positive (Li & Feng, 2015). Some studies suggest that online advisors are especially blunt and directive (Ruble, 2011), but others indicate that members of online communities are motivated to be polite and empathic when delivering advice to each other (Harrison & Barlow, 2009).

Advice received online has a significant impact. It can empower recipients in a variety of ways, including enhancement to self-esteem and confidence, reduction in emotional distress, improvements in coping, and motivation for action (for reviews, see Barak et al., 2008; Feng et al., 2018). However, these outcomes depend, at least in part, on recipients’ trust in the advice they receive. The staged model of trust in online health advice (Sillence & Briggs, 2015) contends that such trust is developed in two stages. First, support seekers develop an impression of trustworthiness based on features of the online environment, including website layout, advertising, and response time. Second, provided a favorable impression of the platform is reached, support seekers evaluate the credibility of the advisor, the personalization of the advice, and familiarity with the recommended actions. In some respects, this perspective on online advice parallels the perspective offered by advice response theory (MacGeorge, Guntzviller, Hanasono, et al., 2016), suggesting that evaluation of source characteristics (which in the online environment, starts with the platform) precedes and influences evaluation of advice content (Feng et al., 2018).

Advice Across Cultures

Although the research base is relatively limited, there is good evidence that the exchange and impact of advice is influenced by culture (for a more extensive review, see Feng & Feng, 2018). This is unsurprising, given contemporary understanding of culture as a broad-ranging, diffuse phenomenon involving attitudes, beliefs, conventions, assumptions, and values (Spencer-Oatey, 2000). To date, most research on advice and culture has focused on comparing advice exchange and evaluation in cultures associated with national or ethnic groups and has often been informed by Hofstede and colleagues’ (2010) work on dimensions of culture, especially the dimension of individualism-collectivism. This research indicates that members of individualistic cultures (e.g., European Americans) are more likely to seek advice and support from others during times of stress than are members of collectivistic cultures (Feng & Feng, 2018). Members of collectivistic cultures appear to find seeking advice more stressful than not seeking it (Taylor, Welch, Kim, & Sherman, 2007). Further, members of collectivistic and individualistic cultures may differ in their motives for advice seeking. For example, Ji et al. (2017) found that East Asians were more likely than Canadians to seek advice for relational reasons, such as establishing, maintaining, or improving a relationship, whereas Canadians were more likely to seek advice for informational reasons, such as obtaining information, solving the problem, or getting an alternative perspective.

Individualism and collectivism also appear to influence advice giving. Generally, studies indicate that members of individualist cultures tend to be more concerned about the face threat associated with giving advice and correspondingly give less advice to others than members of collectivist cultures. For example, Russians are more likely to give advice and view it as more supportive than European Americans (Chentsova-Dutton, 2012; Chentsova-Dutton & Vaughn, 2011), probably connected with the cultural value Russians place on practical information and interdependence. Similarly, Chinese regard several positive outcomes of advice as more likely than Americans do, including providing a different perspective, helping to boost confidence, and relieving stress; Chinese also view negative outcomes such as creating defensiveness and anger as less likely than Americans (Feng, Zhang, Huang, & Hong, 2016).

With regard to evaluating advice, studies suggest a pattern of small, theoretically interpretable cultural differences within a larger context of substantial cross-cultural similarity. In a study testing advice response theory in Chinese and American samples (Feng & Feng, 2013), advice outcomes for both groups were influenced by the content of the advised action (perceived efficacy, feasibility, and limitations), as well as by the advisor’s expertise, trustworthiness, and likability, and the influence of the source factors was mediated through content. Nonetheless, there were some differences. Americans’ advice outcomes were influenced more heavily by perceptions of advice content than were Chinese, whereas Chinese were more strongly influenced than Americans by source characteristics. Further, the influence of source characteristics had both a direct and a mediated influence for Chinese, whereas the influence of source was only mediated through content for Americans. A second study testing propositions from the integrated model of advice (Feng, 2009) similarly found that both Chinese and Americans evaluated the emotional support/problem analysis/advice sequence more positively than alternative sequences, but the strength of this difference was stronger for Americans than Chinese (Feng, 2014).

Discussion of the Literature

Theory and research on the communication of advice reflects a confluence of scholarship from communication, psychology (especially industrial-organizational and social psychology), and several other disciplines (for more extensive reviews, see MacGeorge, Feng, et al., 2016; MacGeorge & Van Swol, 2018a). In the communication discipline, focused research on advice emerged in the mid-1990s within the broader study of supportive communication (MacGeorge, Feng, & Burleson, 2011), owing principally to Goldsmith’s pioneering reflections on the face threats associated with certain kinds of supportive behaviors (Goldsmith, 1994; Goldsmith & Fitch, 1997), and the possibility of strategically ameliorating these threats with linguistic strategies (i.e., facework or politeness; Goldsmith, 2000; Goldsmith & MacGeorge, 2000) to improve the perceived quality of the advice. During approximately this same period of time, scholars in psychology were developing their experimental, laboratory-based paradigm—the Judge-Advisor System—for examining how characteristics of advisors (and to a lesser extent, recipients or messages) influence advice utilization and decision quality (Sniezek & Buckley, 1995; Sniezek et al., 1990; Sniezek & Van Swol, 2001). Key variables included advisor expertise, confidence, and trustworthiness, as well as whether the advice was “cued” (i.e., provided before or after the recipient had the opportunity to independently generate a decision).

From these origins, communication scholars segued to giving more central attention to the content of advice (qualities of the actions being advised) and to a broader range of persuasive and supportive outcomes (Feng, 2009; Feng & MacGeorge, 2010; MacGeorge et al., 2004). In addition, drawing from the psychological tradition, they also began to incorporate greater focus on characteristics of the advisor. Advice response theory (ART) was developed as a synthesis of theory and findings from both traditions, placing advisor characteristics principally in the role of influencing advice evaluation, which in turn drives outcomes (Feng & Feng, 2013; Feng & MacGeorge, 2010). Most of these studies relied on the “message evaluation” paradigm or on questionnaires assessing perceptions of past advising interactions in close relationships. At the same time, psychologists continued to explore an ever-broader range of influences on advice utilization in laboratory contexts, including decision type and difficulty (Gino & Moore, 2007; Van Swol, 2011), and emotional state (Gino & Schweitzer, 2008).

From approximately 2010 onward, communication research on advice has taken an increasingly “interactional turn,” focusing on behaviors that co-occur with advice and their sequencing (Guntzviller, 2018; MacGeorge, Feng, et al., 2016). The integrated model of advice was developed based on findings indicating that advice has its most positive effects in supportive interactions when preceded by emotional support and problem analysis (Feng, 2009; Feng, 2014). Research is beginning to specify how argumentation and framing by the advisor influence reception of advice (Jang & Feng, 2017; MacGeorge, Guntzviller, Branch, et al., 2016), as does recipients’ own planning behavior during interaction (MacGeorge et al., 2015). In part, the shift to focus on interaction has been informed by conversation and discourse analysis of naturally occurring advice interactions (Limberg & Locher, 2012), conducted by scholars from sociology, education, and other disciplines (e.g., Waring & Song, 2018) and highlighting the range of interactional strategies used to present, defend, accept, and resist advice (Hepburn, Shaw, & Potter, 2018) . This shift has also necessitated methodological innovations, including more sophisticated designs for message evaluation studies (Feng, 2009; Feng, 2014) and the recording of naturalistic advising interactions in laboratory contexts (MacGeorge, Guntzviller, Hanasono, et al., 2016).

Consistent with this focus on interaction, scholars in both communication and psychology are currently placing increased emphasis on studying advising with an explicit focus on relational context and influence (Branch & Dorrance Hall, 2018), and understanding advising from the perspective of the advisor (Blunden & Gino, 2018), including how misalignment between advisor and advisee contributes to dissatisfaction with advising interactions (Guntzviller et al., 2017). At the same time, scholars who study organizations are building on methodological innovations in social network analysis to advance research on advice networks and transactive memory systems (Yuan, Carboni, & Ehrlich, 2010). Other future areas of focus for research on advice appear likely to include greater convergence between research on advice in dyads and research on advice in networks and organizations (Feng et al., 2016), and increasing synergy between theory development and application to advising problems in real-world contexts (e.g., MacGeorge, Smith, et al., 2017; Prahl & Van Swol, 2017).

Further Reading

Bonaccio, S., & Dalal, R. S. (2006). Advice taking and decision-making: An integrative review of the literature. Organizational Behavior and Human Decision Processes, 101, 127–151.Find this resource:

    Bonaccio, S., & Van Swol, L. (2014). Combining information and judgments. In S. Highhouse, R. S. Dalal, & E. Salas (Eds.), Judgment and decision making at work (pp. 178–198). New York, NY: Routledge.Find this resource:

      de Hooge, I. E., Verlegh, P. W. J., & Tzioti, S. C. (2013). Emotions in advice taking: The roles of agency and valence. Journal of Behavioral Decision Making, 27, 246–258.Find this resource:

        Feng, B. (2009). Testing an integrated model of advice-giving in supportive interactions. Human Communication Research, 35, 115–129.Find this resource:

          Feng, B. (2014). When should advice be given? Assessing the role of sequential placement of advice in supportive interactions in two cultures. Communication Research, 41(7), 913–934.Find this resource:

            Goldsmith, D. J. (1994). The role of facework in supportive communication. In B. R. Burleson, T. L. Albrecht, & I. G. Sarason (Eds.), Communication of social support: Messages, interactions, relationships, and community (pp. 29–49). Thousand Oaks, CA: SAGE.Find this resource:

              Goldsmith, D. J., & Fitch, K. (1997). The normative context of advice as social support. Human Communication Research, 23, 454–476.Find this resource:

                Guntzviller, L. M., MacGeorge, E. L., & Brinker, D. L. (2017). Dyadic perspectives on advice between friends: Relational influence, advice quality, and conversation satisfaction. Communication Monographs, 84, 488–509.Find this resource:

                  Limberg, H., & Locher, M. A. (Eds.). (2012). Advice in discourse. Amsterdam, The Netherlands: John Benjamins.Find this resource:

                    MacGeorge, E. L., Feng, B., & Guntzviller, L. M. (2016). Advice: Expanding the communication paradigm. In E. L. Cohen (Ed.), Communication yearbook (Vol. 40, pp. 213–244). New York, NY: Routledge.Find this resource:

                      MacGeorge, E. L., Guntzviller, L. M., Hanasono, L. K., & Feng, B. (2016). Testing advice response theory in interactions with friends. Communication Research, 43, 211–231.Find this resource:

                        MacGeorge, E. L., & Van Swol, L. M. (Eds.). (2018). The Oxford handbook of advice. New York, NY: Oxford.Find this resource:

                          Sniezek, J. A., & Buckley, T. (1995). Cueing and cognitive conflict in Judge-Advisor decision making. Organizational Behavior and Human Decision Processes, 62, 159–174.Find this resource:

                            Van Swol, L. M. (2011). Forecasting another’s enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice. International Journal of Forecasting, 27, 103–120.Find this resource:

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                                              Bonaccio, S., & Dalal, R. S. (2006). Advice taking and decision-making: An integrative review of the literature. Organizational Behavior and Human Decision Processes, 101, 127–151.Find this resource:

                                                Branch, S. E., & Dorrance Hall, E. (2018). Advice in intimate relationships. In E. L. MacGeorge & L. M. V. Swol (Eds.), The Oxford handbook of advice (pp. 91–110). New York, NY: Oxford University Press.Find this resource:

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                                                                      de Hooge, I. E., Verlegh, P. W. J., & Tzioti, S. C. (2013). Emotions in advice taking: The roles of agency and valence. Journal of Behavioral Decision Making, 27, 246–258.Find this resource:

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                                                                                    Feng, B., & Burleson, B. R. (2008). The effects of argument explicitness on responses to advice in supportive interactions. Communication Research, 35, 849–874.Find this resource:

                                                                                      Feng, B., & Feng, H. (2013). Examining cultural similarities and differences in responses to advice: A comparison of American and Chinese college students. Communication Research, 40, 623–644.Find this resource:

                                                                                        Feng, B., & Feng, H. (2018). Advice across cultures. In E. L. MacGeorge & L. M. V. Swol (Eds.), The Oxford handbook of advice (pp. 381–402). Oxford, U.K.: Oxford University Press.Find this resource:

                                                                                          Feng, B., & MacGeorge, E. L. (2006). Predicting receptiveness to advice: Characteristics of the problem, the advice-giver, and the recipient. Southern Communication Journal, 71(1), 67–85.Find this resource:

                                                                                            Feng, B., & MacGeorge, E. L. (2010). The influences of message and source factors on advice outcomes. Communication Research, 37, 576–598.Find this resource:

                                                                                              Feng, B., & Magen, E. (2016). Relationship closeness predicts unsolicited advice giving in supportive interactions. Journal of Social and Personal Relationships, 33, 751–767.Find this resource:

                                                                                                Feng, B., Zhu, X., & Malloch, Y. Z. (2018). Advice communication in cyberspace. In E. L. MacGeorge & L. M. V. Swol (Eds.), The Oxford handbook of advice (pp. 363–380). Oxford, U.K.: Oxford University Press.Find this resource:

                                                                                                  Feng, H., Zhang, W., Huang, W., & Hong, S. (2016). A mediation model of giving advice intention across two cultures. Intercultural Communication Studies, 25(3), 168–212.Find this resource:

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                                                                                                            Gino, F., & Schweitzer, M. E. (2008). Blinded by anger or feeling the love: How emotions influence advice taking. Journal of Applied Psychology, 93, 1165–1173.Find this resource:

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                                                                                                                        Guntzviller, L. M. (2018). Advice messages and interactions. In E. L. MacGeorge & L. M. V. Swol (Eds.), The Oxford handbook of advice (pp. 69–90). Oxford, U.K.: Oxford University Press.Find this resource:

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