What is a hyperpersonal relationship

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Developing an Optimal Match Within Online Communities: An Exploration of CMC Support Communities and Traditional Support

By Jeanine Warisse Turner, Jean A. Grube, and Jennifer Meyers

This study investigates the complementary nature of face-to-face and computer- mediated social support and the development of a context through which hyperpersonal communication can develop within online communities. Optimal matching theory is used as a framework for explaining how hyperpersonal com- munication develops within online cancer support communities. We compared online participants’ perceptions of illness support from the list with the support they received from a nonmediated relationship. Respondents participated more within the online community only when they perceived that the depth and support that they received from the online community was high, and when the depth and sup- port they received from the specific person in their life was low.

I opened my email to a whole new family today. There were so many letters. . . . Can you know how great it is to find someone who knows what I have been through . . . it is so good to know that there is someplace I can go where I can talk freely about my concerns and fears and KNOW that someone under- stands. (Anonymous, illness-related listserv, April 23, 1998)

Online medical information and support groups are changing the nature of rela- tionships that patients have with the people around them. A 1998 survey found that 30.8 million people (or 46% of online users) sought information via the Internet about a medical or personal problem (Green & Himelstein, 1998). In fact, Lamberg (1997a) argued that health chat rooms and discussion groups are among the most widely visited sites in cyberspace. This relatively recent outlet for communication

Jeanine Warisse Turner is an assistant professor at the McDonough School of Business, Georgetown University, and an adjunct research assistant professor, Georgetown University Medical Center; Jean A. Grube is a healthcare consultant in Maryland; and Jennifer Meyers is an administrative assistant, Tar- geted Genetics in Washington, DC. The authors wish to thank two anonymous reviewers for their valuable comments on earlier drafts of this manuscript. An earlier version of this paper was presented at the 1999 National Communication Association annual conference in Chicago, IL.

Copyright © 2001 International Communication Association

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and support has created new opportunities to explore why people choose to seek virtual contexts. Thus, we may begin to understand the nature of the relationship that leads to the development of hyperpersonal communication within computer- mediated communication (CMC).

Walther (1996) introduced the construct of hyperpersonal communication to describe the strong, personal relationships and exchanges that take place within some CMC. Research has explored the existence of hyperpersonal communication and described how the characteristics of CMC give rise to this existence. Hyperpersonal communication theory of CMC offers a process-based explanation of how CMC relationships come to be more rewarding than parallel face-to-face relationships under certain circumstances. What is less well known is how the context may prompt or motivate such relational communication processes. The present research adds this contextual dimension to the framework by showing how certain contexts may provide opportunities for hyperpersonal relationships to develop. Specifically, the study explores users’ involvement in CMC networks in contrast with some of their unmediated social contacts to better understand the opportunities offered and relationship resources available through CMC.

In this study, we investigate the development of hyperpersonal communication within the context of online communities devoted to cancer support. In doing so, we expand on Cutrona and Russell’s (1990) theory of optimal matching, which suggests that certain forms of support may be most beneficial following specific types of stress. Through the study of these online communities we suggest that online communities can provide an opportunity for optimal matching to occur, thus creating a context for hyperpersonal communication. The context of this study examines online participants’ perceptions of illness support from the list in conjunction with the illness support they received from a specific significant indi- vidual within their personal lives.

This study constitutes one of the few field studies of its kind that directly com- pares illness-related support from an online support group with support from a significant person within an individual’s life (McCann, 1998; see also Mickelson, 1998).

Literature Review

Hyperpersonal Communication Research following online communication has moved from defining asynchro- nous CMC as an impersonal, lean medium (see reviews in Garton & Wellman, 1995; Walther, 1994), to showing how CMC can support interpersonal interactions (Baym, 1995; Braithwaite, Waldron, & Finn, 1999; Rheingold, 1993; Walther, 1995). In reviewing and expanding on these research findings, Walther (1996) suggested that CMC environments could be impersonal, interpersonal, and hyperpersonal. Impersonal CMC characterizes exchanges that are primarily task-based with little social interaction. Interpersonal CMC describes socially oriented exchanges be- tween users. Finally, Walther (1996) created the construct hyperpersonal to de- scribe and extend understanding of the depth of interpersonal exchanges within

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CMC. Hyperpersonal communication describes the type of CMC “that is more socially desirable than we tend to experience in parallel face-to-face interactions” (Walther, 1996, p. 17). Walther (1996) proposes four characteristics of the medi- ated environment that may contribute to hyperpersonal communication: (a) the idealized perception of the receiver, (b) the optimized self-presentation of the sender, (c) asynchronous channels supporting information management, and (d) a feedback loop allowing intensification magnified in minimal-cue interaction. In effect, Walther (1996) suggests that hyperpersonal communication may occur within CMC based on senders’ and receivers’ reciprocal and hyperbolic construction of each other and their relationship, within a minimal cues environment.

This exaggerated sense of the relationship is built on social identity- deindividuation (SIDE) theory. SIDE theory predicts that in the absence of face-to- face cues and prior personal knowledge, social context cues present in CMC take on particular value and may lead to overattribution of similarity (Walther, 1996). Walther (1996) argued that CMC is hyperpersonal when “users experience com- monality and are self-aware, physically separated, and communicating via a lim- ited-cues channel that allows them to selectively self-present and edit; to construct and reciprocate representations of their partners and relations without the inter- ference of environmental reality” (p. 33). In addition, the asynchronous nature of CMC allows participants to plan their responses more mindfully than in spontane- ous, real-time talk (Hiemstra, 1982).

Online support groups provide a ripe context for the development of hyperpersonal communication because participants who join and become involved in an online group already are assuming a common identity with other group members. An individual assumes the identity of having a particular problem or concern and assumes that other online members share a similar identity. Messages that are exchanged within the online group reinforce this similar identity. There- fore, this context, coupled with the anonymity and opportunity for planned re- sponses provides a ripe environment for senders to initiate interactions with hyperpersonal potential.

Although these characteristics of CMC provide the opportunity for hyperpersonal communication to take place, all CMC is not hyperpersonal. One theory that pro- vides a foundation for understanding the context through which these hyperpersonal communication relationships develop is optimal matching theory.

Optimal Matching Theory Optimal matching theory argues that social support is a multidimensional con- struct and that certain types of social support may be most effective when matched with certain types of stressful incidents (Cutrona & Russell, 1990). Cutrona and Russell’s theoretical model suggests that three characteristics of life events: desir- ability, controllability, and domain (whether the stressor is related to assets, re- lationships, achievement, or social roles) determine the types of support required for positive health outcomes to occur. Of these characteristics, the most influential determinant of social support needs was controllability. Uncontrollable events necessitate more emotional support whereas controllable events require more instrumental support.

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Coping with medical illness, specifically an illness that is life threatening, can be categorized as a negative and uncontrollable event requiring emotion-focused coping to address the fear, anger, and depression that can result from a serious illness (Cutrona & Russell, 1990). Both Bloom (1982) and Dimond (1979) found that emotional support and esteem support were associated with fewer declines in social functioning and, in Dimond’s (1979) study, fewer medical problems.

Optimal matching theory suggests that a person’s development of a medical illness creates a strong need for social support. Furthermore, as an illness consti- tutes an uncontrollable event that may influence several domains of an individual’s life (income, contact with others, sense of achievement, physical capacity), sup- port from others that responds to each of these domains can help achieve optimal adjustment (Cutrona & Russell, 1990). Unfortunately, available support from oth- ers who understand the impact of the illness on these various life domains is not always available. Individuals may not be able to attend a support group targeted at their specific needs. However, with the advent of online support communities addressing specific concerns within individuals’ lives, and the thousands of par- ticipants within these communities, the mathematical probability of a person find- ing someone with the same illness and treatment alternatives increases exponen- tially. For example, a patient can return home from being diagnosed, log in to an online community concerning the diagnosis, and ask about treatment alternatives or just express concern. Within minutes, that patient can receive specific responses to the posting. Similarly, the patient can learn about the diagnosis simply by reading the discussions taking place. The participants within online communities provide receptivity, interest, and disclosure, despite that they are strangers other- wise, because they can share a critical commonality. Therefore these large groups provide a strong probability that participants can find one or many other individu- als who share similar specific symptoms, treatments, reactions, problems, and challenges.

This research compares the support offered by a specific significant relation- ship within an individual’s life to the support offered by an online community. Such comparisons allow us to examine the extent to which the existence or char- acteristics of other outlets of support may influence the potential of a participant to develop a hyperpersonal relationship within an online community. This em- phasis is particularly important since much of past social support research in traditional environments (or “non-online communities”) focused on single rela- tionship designs, which may neglect “the possible effects that other relationships might have on the nature of the relationship under investigation, as well as im- pacts that the relationship being studied might have on other relationships” (Sarason, Sarason, & Pierce, 1994, p. 249).

Communicating Support Online Camosy (1996) defines a support network as “a group of people devoted to pro- motion of proper diagnosis, treatment, and prevention of a specific condition, primarily through patient education and support” (p. 278). Most patients are look- ing for encouragement from someone who has been through the same illness or has experienced similar treatment. Whereas patients used to be limited to face-to-

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face groups to receive this support, the advent of the Internet and online listservs has created an online alternative.

Email and the Internet are renegotiating the boundaries of communication within medical-related discussion groups. Patients can share personal stories, medical information, and support with other patients experiencing similar concerns. Re- searchers have found that CMC discussion groups have provided new avenues of social support for patients (see, for example, Braithwaite, Waldron, & Finn, 1999; Brennan, Moore, & Smythe, 1992; Lamberg 1997b; Lieberman, 1992; Mickelson, 1998; and Scheerhorn, Warisse, & McNeilis, 1995).

Individuals join a social support online community because they are seeking information, empowerment, encouragement, emotional support, and empathy re- garding their specific concern (Hamilton, 1998; Mickelson, 1998; Scheerhorn et al., 1995; Sharf, 1997). An individual does not have to travel physically to partici- pate. Online communities can provide this support wherever the individual is located. Having other people share very similar concerns within the comfort and convenience of a patient’s own home, office, and so forth, provides a strong incentive for online participation. In addition, some of the other characteristics of online communication (e.g., anonymity, self-presentation, and idealized “other”) make CMC support groups within illness-related communities a welcome alterna- tive to traditional support groups in face-to-face environments (Scheerhorn et al.; Walther & Boyd, in press). Another advantage of online discussion groups within illness-related communities is availability. Participants are free to post 24 hours a day, 7 days a week. Since patients may be awake in the middle of the night due to their illness or anxiety associated with their illness, access to a community of people who can provide comfort and company day or night is important (Scheerhorn et al.; Walther & Boyd, in press).

Another advantage of online communities is their ability to provide “weak tie” support. Weak-tie relationships exist outside the pressures and dynamics of close family relationships and often are contextual in nature (Adelman, Parks, & Albrecht, 1987). A person goes to a specific place to receive weak-tie support. This place might be a church to talk to a priest or an online community to talk with other sufferers of a similar illness. In fact, some researchers suggest that the support offered by weak ties can provide anonymity and objectivity not found in close personal relationships, thus providing a helpful alternative for social support (Adelman et al.; Walther & Boyd, in press; Wellman & Gulia, 1999).

Mediated channels create many opportunities for support from weak-tie rela- tionships. Researchers studying telephone hotlines as a context for weak ties sug- gested that the channel provided added support because callers could remain anonymous, take greater risks in expressing feelings, have immediate access 24- hours a day, and not be limited by geographic barriers (Adelman et al.,1987). Wellman and Gulia (1999) and Walther and Boyd (in press) support the concept that online communication fosters development of weak ties because discussion often concentrates on the topic most salient to the user. In addition, more exper- tise may be brought to bear on the problem because such groups tend to be more heterogeneous relative to strong-tie groups of close personal relations.

As optimal matching theory suggests, uncontrollable events like the develop-

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ment of an illness requires support specific to the losses involved (Cutrona & Russell, 1990). In general, illness-related online support communities may provide a form of empathy and support to patients that may not be available from strong- tie connections by offering a deeper understanding of fears, feelings, and family reactions associated with the illness.

Finally, the sheer numbers of people participating in online support groups mathematically suggests the possibility for individuals to find a match with their specific type of illness or diagnoses regimen. With literally hundreds of individu- als subscribing at any one time to a specific listserv or electronic bulletin board (as compared with 10 or 11 individuals in a face-to-face support group), the likeli- hood of meeting others experiencing a similar context increases.

Measuring Support This research adopts an interactional-cognitive perspective to the study of support in that we study behavior in the context of situational, intrapersonal, and interper- sonal factors (Sarason et al., 1994). This perspective argues that social support is the product of a person’s experience interacting with individuals in a variety of situations. These experiences shape an individual’s behavior and their assessment of support within specific situations. The present research compares participants’ experience with support from the listserv with their experience receiving support from a significant other person in face-to-face interactions. We will refer to this significant other as a “face-to-face partner” throughout this paper.

The Quality of Relationships Inventory The Quality of Relationships Inventory (QRI) was developed to assess three fea- tures of close relationships: support, depth, and conflict (Pierce, Sarason, & Sarason, 1991; Pierce, 1994). The support dimension “reflects the extent to which the rela- tionship participant believes that a specific individual is available to provide assis- tance across a variety of situations.” The depth dimension “reflects the perceived importance of the relationship.” Finally, the conflict dimension “reflects the per- ceptions of conflict that a relationship participant has regarding a specific indi- vidual” (Pierce, 1994, pp. 250–251). For this study, we examined both support and depth dimensions.

The QRI helps us to explore optimal matching theory as a context for hyperpersonal communication by comparing distinct dimensions of online and face-to-face relationships, thereby increasing our understanding of the context through which hyperpersonal communication develops. The support dimension allows us to explore the explicit function of the listserv, and the depth dimension helps us to operationalize hyperpersonal communication by exploring the extent to which participants feel their relationship with the listserv is significant and that others in the listserv are committed to the relationship as well.

The QRI is a reliable and valid measure that allows us to investigate the role of specific features of relationships within a specific interpersonal context (Pierce, 1994). This perspective is critical in that it allows researchers to target specific relationship types and their connection to specific outcomes (Sarason, Sarason, & Gurung, 1997). Within the present study, we use the QRI to explore the relation-

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ship that the participant has with a specific individual that provides them support regarding their illness, as well as the relationship the participant has with their specific listserv. Although the QRI was created to be used in conjunction with a singular relationship, rather than a collection of relationships (like “the list”), dis- cussions with the QRI’s creator suggested that its use with a list could be appropri- ate. Additionally, we were interested in participants’ relationship with the list in general as opposed to their relationship with a specific person on the list. Because participants post to “the list” and read messages from “the list,” we proposed that participants would be able to target the list as the focus of support (G. R. Pierce, personal communication, February 3, 1998).

Research Hypotheses

Optimal Matching Theory as a Framework for Understanding Hyperpersonal Communication and Its Influence on Behavior Past research has investigated the development of supportive CMC communities and has explored the characteristics of these communities. However, no research has explored the contexts that may lead to an individual’s willingness to engage in specific behaviors within a CMC community and thus hyperpersonal communica- tion. This study explores one contextual variable—the nature of the relationship with a significant face-to-face partner—and its influence on the development of hyperpersonal communication within online communities.

Direct comparison between the list and face-to-face partner. Although recent research suggests that online communities can provide support for people with illness, it is unclear how such support compares to more traditional face-to-face support. Therefore, we explore this as a research question:

RQ1a: How do participants’ perceptions of support from the listserv differ from the perceived support received from their face-to-face partner?

RQ1b: How do participants’ perceptions of depth from the listserv differ from the perceived depth received from their face-to-face partner?

Building on assumptions of optimal matching theory, we suggest that participants who find a more socially acceptable support environment online than they do from their conventional, face-to-face sources of support may turn to online sup- port more often. We explore this by first looking at the relationship between support and the amount of time spent reading. Next, we examine the relationship between the time spent reading, posting, seeking private relationships online and face-to-face, and the influence of these face-to-face interactions on online activity.

Time spent reading. Research has found that isolation may predict online par- ticipation. One study of online single mothers with young infants found that a participant’s degree of social isolation predicted his or her likelihood of participat- ing in the online community. The more socially isolated the participants felt from their peer group, the more likely they were to participate in online discussions

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(Dunham, Hurshman, & Litwin, 1998). Cancer patients, with few peers experienc- ing the same concerns, also would feel socially isolated. Therefore, their initial motivation for getting onto a listserv may be to find some source of support, either in the form of information or more relational support. Subsequently, the more support that individuals receive from the list, the more time they will spend read- ing messages within an online community.

H1a: As an individual’s perception of support from the list increases, so does the amount of time spent reading.

Albrecht, Burleson, and Goldsmith (1994) note, however, that “individuals en- gaged in supportive relationships do not exist in a vacuum” (p. 439). Other rela- tionships within the social network of an individual’s life influence their percep- tions and behavior in any one relationship. Therefore, we suggest that the nature of the relationship between perceived online support and time reading is moder- ated by the amount of perceived support received from an important face-to-face partner regarding the user’s illness.

H1b: As the magnitude of the relationship between perceived online support and amount of time reading increases, support from an individual’s face-to- face partner decreases.

Time spent reading, posting, and seeking private email relationships. Although the individual initially may seek support in the form of information, online inter- action can create more personal relationships within an online community. These personal relationships then can be broadened through use of other channels as well (Parks & Floyd, 1996). As individuals become more actively involved in a listserv they are more likely to increase their postings, as well as develop relation- ships with members of the list offline (Parks & Floyd). Similarly, we argue that the deeper the relationship that individuals perceive with the list, the more likely they will be to spend time reading and posting. Additionally, as participants’ relation- ship with the list moves from impersonal information gathering to more relationally oriented communication, these participants may expand their communication with a general “anonymous” list to developing personal communication with specific individuals through private email.

H2a: There is a positive relationship between perceived depth from the list and the amount of time an individual spends reading.

H3a: There is a positive relationship between perceived depth from the list and the number of people contacted by private email.

H4a: There is a positive relationship between perceived depth with the list and the number of times an individual posts.

We predict that this movement toward a deeper relationship with the list and development of specific relationships through private email is more likely when

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the relationship with the user’s face-to-face partner is lacking in depth specific to his or her illness.

H2b: As the magnitude of the relationship between perception of depth with the list and the amount of time spent reading increases, the perceived depth with the user’s face-to-face partner decreases.

H3b: As the magnitude of the relationship between perception of depth with the list and the number of private emails increases, the perceived depth with the user’s face-to-face partner decreases.

H4b: As the magnitude of the relationship between perception of depth with the list and the number of postings increases, the perceived depth with the user’s face-to-face partner decreases.

Influence of face-to-face interaction on online activity. Parks and Floyd (1996) suggest the “relationships that begin online rarely stay there” (p. 92). Therefore, we suggest that as a deeper relationship with the list evolves, these individuals will be more likely to meet face-to-face with individuals from the list.

H5: There is a positive relationship between depth with the list and the num- ber of listserv participants who met face-to-face.

Finally, we speculate that meeting face-to-face will increase an individual’s com- mitment to and involvement with the list relative to those who have not made face-to-face contact. The behavioral manifestations of such commitment and in- volvement will be more time spent reading, staying in contact via private email, posting more frequently, and electing not to go “no mail” relative to subjects who have not made face-to-face contact. When participants go “no mail,” they explic- itly post that they will be away and not have access to the list for a specific period of time.

H6: Individuals who have made face-to-face contact spend more time reading, post more often, stay in contact with individuals through private email, and are less likely to go “no mail” relative to those individuals who have not made such contact.

Methods

Survey Predictor variables. As previously discussed, we used the QRI results to illustrate the contrast between support received face-to-face and that received from CMC relationships to identify contexts through which CMC offered the potential for hyperpersonal communication. Part 1 of the survey directed the participants to respond to the statements concerning support and depth with the list in mind. Part 2 directed the participants to answer the same questions with a specific per- son who provided face-to-face support in mind.