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Getting “plugged in”: A networkanalysis of health‐informationseeking among “stay‐at‐homemoms”Rebecca W. Tardy a & Claudia L. Hale ba Assistant Professor of Communication , University ofLouisville ,b Professor at the School of Interpersonal Communication ,Ohio University ,Published online: 02 Jun 2009.

To cite this article: Rebecca W. Tardy & Claudia L. Hale (1998) Getting “plugged in”: Anetwork analysis of health‐information seeking among “stay‐at‐home moms”, CommunicationMonographs, 65:4, 336-357, DOI: 10.1080/03637759809376457

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Getting "Plugged in":A Network Analysis of Health-Information

Seeking Among "Stay-At-Home Moms"

Rebecca W. Tardy and Claudia L. Hale

This report focuses on health-oriented conversations evident in informal, interpersonalnetworks. This study was an investigation of the network structure, the nature of relationships,the contents of interactions, and the impact of support manifested in a "stay-at-home " mothers'toddlers' playgroup. Diffusion of innovations theory (Rogers, 1983) sewed as the theoreticaland organizational lens. Members' roles, as well as characteristics of opinion leaders, wereidentified via sociograms and enriched with anecdotal evidence from personal interviews andparticipant observation. Ideas regarding how institutions can utilize this information and thesenetworks are offered. Key Words: Network Analysis, Women's Health, Diffusion ofInnovations, Health Information-Seeking

Introduction

When one thinks about research and theory development concerning healthcommunication, the initial image that comes to mind is probably that of work

concerning either interactions between a practitioner and patient (e.g., Ballard-Reisch, 1990; Beisecker, 1990; Burgoon, Parrott, Burgoon, Coker, Pfau, & Birk,1990; Conlee & Vagim, 1992; Geist & Hardesty, 1990; Klingle, 1990; O'Hair, 1989;Street, 1989, 1991; Thompson, 1981) or mass-mediated campaigns, especially withregard to cancer and AIDS (e.g., Edgar, Fitzpatrick, & Freimuth, 1987; Freimuth,1987, 1992; Freimuth, Stein, & Kean, 1992; Johnson, Meischke, Grau, & Johnson,1990; Markova & Power, 1992). In reality, however, a great deal of conversationaffecting health-care decisions occurs outside the formal institutions of long-term andacute care facilities, physicians' offices, televised reports, and magazine articles. AsNussbaum (1989) observes, "Many of us discuss our own health or health-relatedissues with our family and friends at home or in restaurants or on a softball field" (p.36). McKnight (1988) and Arntson (1989) echo this sentiment and argue that weneed to develop a richer understanding of how personal and professional relation-ships, economic conditions, and physical environment affect health decisions andindividual health related behavior.

While not denying the importance of the physician-patient relationship, there is aneed for a greater understanding of the language and culture of health communica-tion as that communication occurs outside formal medical environments and relationships. Ifpatient empowerment is a desired goal, as is advocated by many commentators/theorists (see, for example, Ballard-Reisch, 1990, 1993; Beisecker, 1990; Schneider& Tucker, 1992), then we need to expand our understanding of the language of"health consumerism" from the standpoint of the consumer, as opposed to that of

Rebecca W. Tardy (Ph.D., 1994, Ohio University) is Assistant Professor of Communication at the Universityof Louisville. Claudia L. Hale (Ph.D., 1976, University of Illinois) is Professor at the School of InterpersonalCommunication at Ohio University. This study is one portion of the first author's dissertation, directed by thesecond author; an earlier version was presented at the annual convention of the International CommunicationAssociation, Albuquerque, NM, May, 1995. The authors wish to extend gratitude to Dr. Dennis Gouran andanonymous reviewers for their suggestions, revisions, and contributions.

COMMUNICATION MONOGRAPHS, Volume €5, December 1998

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the medical establishment. The fact is that informal interpersonal networks are richand potentially influential arenas for health-related communication. Individuals relyon their social networks for information concerning health practices; however, thesenetworks have been largely neglected as sites for health communication research.

The purpose of the research reported in this article was to contribute to thatexpanded understanding of health communication by investigating what is essen-tially the daily, lived experiences and perceptions of health (and illness) within adefined group of interactants. Even more specifically, it was to demonstrate howhealth information-seeking within an informal, interpersonal network can be boththeoretically conceptualized and investigated.

Health Information-Seeking in Informal, Interpersonal Networks

Health information-seeking, as a construct, appears in essentially two distinctivebodies of scholarship: channel selection research and social support research. Froma mass media perspective, Johnson et al. (1990) define information-seeking as "thepurposive acquisition of information from selected channels" (p. 1). Freimuth andcolleagues (Edgar, Fitzpatrick, & Freimuth, 1992; Freimuth, 1987; Freimuth, Stein, &Kean, 1989) rely on Dervin's (1978) view of information as serving a sense-makingfunction. External information is sorted through internal processes that distinguishuseful or helpful ideas from those that should be discarded. Levanthal, Safer, andPanagis (1983) likewise propose that people construct "common-sense" models oftheir illness on the basis of a combination of present and past experience, as well asinformation obtained from the media, various health care providers, and interper-sonal networks, including family and friends. Indeed, channel selection research(e.g., Connell & Crawford, 1988; Johnson et al., 1990) reveals that physicians,organizations, and friends/family were almost equally represented (37-38%), withsome overlap, as sources of information.

This sense-making and uncertainty reduction role is also evident in social supportresearch (Albrecht & Adelman, 1987). Considering it as a multi-dimensional con-struct, Cutrona, Suhr, and MacFarlane (1990) identify five categories of supportivemessages, including information support, esteem support, tangible assistance, emo-tional support, and network support. House (1981) and House and Kahn (1985)likewise divide social support into four categories: emotional, appraisal, informa-tional, and instrumental. Despite the identification of these various forms of support,when it comes to health issues, the primary area of concern for researchers has beenemotional support in post-diagnosis situations.

Two biases are reflected in this approach. First is a bias in favor of attention tocommunities marked, either personally or via association, by illness. The mundanehealth-related interactions of individuals who are not facing critical illness eitherthemselves or on the part of a loved one have not been of great interest. Second is abias against informational support. Although informational support has been specifi-cally identified as a form of social support, its significance emerges more asserendipitous than as a specific focus of scholarly inquiry. For example, Arntson andDroge (1987) in their research concerning self-help groups and social support(specifically, with respect to epilepsy) found that information-seeking was a strongmotivator for membership. Eighty-seven percent of their respondents claimed thatthey had sought information in the past and were currently interested in newinformation regarding epilepsy. The self-help group meetings, however, focusedmore on fulfilling psychosocial needs than informational needs; thus, members who

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338 COMMUNICATION MONOGRAPHS

were less emotionally involved with their fellow members expressed relative dissat-isfaction with the group. The less satisfied members already had a strong supportsystem (such as family and friends). Their primary reason for joining the groupappears to have been information-seeking, a need that would seem to have goneunmet.

Given our interest in health-information seeking as a commonplace activity, aswell as the biases/limitations noted, for our purposes, we thought it best to conceiveof the construct of health information-seeking as verbal and nonverbal messagesascertained via everyday interaction, either purposeful or serendipitous, by members in aself-defined network, that serve not only to reduce uncertainty regarding health status, but alsoto construct a social and personal (cognitive) sense of health. Our argument for thisconception is that health information-seeking be viewed, both theoretically andmethodologically, as socially supportive messages embedded in everyday conversa-tion or "talk." This perspective is congruent with that of Leatham and Duck (1990)who assert that social support talk is best considered as situated, symbolic, social, andstrategic conversations that serve both to construct reality and to develop relation-ships. Leatham and Duck suggest that researchers investigating social supportshould consider four areas for investigation: the network structure, the nature of therelationships, the content of the interactions, and the impact of support.

In its fullest form, the present study examined how everyday talk, as it occurred inan interpersonal network, defined and affected decisions regarding health status (seealso, Tardy & Hale, in press). The overall study focused on at least three of theseaspects: structure, content, and impact of health information-seeking in informal,interpersonal networks. The inattention to the nature of the relationships should notbe read as a denial of the importance of this area. Rather, in the case of this research,the nature of the relationships was not the intended focus of examination. Instead,the study sought to examine interactional issues apart from questions concerningrelational initiation, maintenance, and/or disengagement.

Diffusion of Innovations Theory

One of the primary challenges facing research efforts of the sort reported herein iscrafting an appropriate answer to the following question: How do we investigate,systematically and theoretically, (health) communication in its most mundane form?Capturing everyday talk is rather like catching fog in a mason jar; it tends to changeform under scrutiny. Nevertheless, a mixture of quantitative and qualitative methodswas used in investigating the structure, content, and impact of health information-seeking among members of an informal, interpersonal network. The theory selectedto guide this study was diffusion of innovations theory (Rogers, 1983). We usednetwork analysis, open-ended surveys, interviews, and participant observation toacquire and assess data. Through triangulation, we were able to develop a sense ofwhat occurs on a day-to-day basis regarding information exchange, as well asdecision-making, as it pertains to health issues.

Diffusion of innovations theory was selected because it provides an explanationfor how information, as an innovation, traverses a social network. However, not onlydoes the theory provide an explanation of the adoption process within a socialsystem, it also explains what precedes the introduction and what occurs afteradoption. That is, it enables one to answer the questions, what is the general "path"of information flow, and how does adoption impact the product or innovation?

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InstitutionalII

Governmental Control/Regulation

Organizational

HSOs Mass Media

Health Services Facilities Official Reports POP Culture

Interpersonal/ProfessionalII

Practitioners

iChange Agents

=== Innovators

Opinion Leaders(Early Majority)

Social Networks/tton - Professional

Late Majority

Cliques Liaisons

Bridges ||"Laggards"

FIGURE 1

DIFFUSION OF INNOVATIONS THEORY AND HEALTH COMMUNICATION: A COMMUNICATION MODEL FORHEALTH INFORMATION-SHARING

Figure 1 provides a view of this process. The traditional concentration of healthcommunication research has been on the upper portion of the depicted flow; thelower portion has been investigated, but mostly from the vantage point of socialsupport groups provision regarding post diagnosis information and emotionalsupport. We sought to clarify HOW the process occurs within the network.

Diffusion of innovations theory (Rogers, 1983) provides a comprehensive interpre-tation of how various channels can be utilized to illuminate the process of informa-tion transmission from formal, institutionalized voices of health services, throughinformal networks, to the individual. Definitionally, diffusion is the "process bywhich an innovation is communicated through certain channels over time amongthe members of a social system" (Rogers, 1983, p. 10). An innovation is an idea,practice, or object that individuals or other units of adoption perceive to be new(Rogers, 1983).l Diffusion theory proposes that the introduction of an innovation byan institution must move through and across various channels until it is adopted andthat people are influenced by their strong and weak interpersonal network ties in

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adopting ideas or innovations. Channels for diffusion exist as the media, cultural,group, and dyadic levels.

While mass media serve an extremely important educational role in conveyinghealth information (e.g., Freimuth, 1987; Freimuth et al., 1989; Johnson et al., 1990,1993), the impact of media in informing large numbers of people is obscured bypersonal consumer characteristics. For instance, as Childers and Post (1975) suggest,the economically disadvantaged share certain characteristics that affect their abilityto utilize mass media sources fully. Namely, they have lower levels of reading andprocessing skills; they are often encapsulated in a closed system or network, whichlimits access to new information; and, they have a tendency toward an external locusof control regarding their ability to resolve their own health issues.

In contrast, more active consumers of mass-mediated messages engage in selectiveexposure, acceptance, and retention of information and have more fully developedcommunicative skills, as well as a greater capacity for storage and comprehension ofnew information, all of which contributes to increased awareness and more relevantsocial contacts (Freimuth et al., 1989). These characteristics are consistent withdiffusion of innovations theory in identifying opinion leadership in interpersonalnetworks (Rogers, 1983). Opinion leadership refers to "the degree to which anindividual is able to informally [sic] influence other individuals' attitudes or overtbehavior in a desired way with relative frequency" (Rogers & Kincaid, 1981, p. 123).Opinion leaders generally have greater social participation and higher socioeco-nomic status, are more cosmopolitan and well educated, and have greater access tochange agents and exposure to mass media than their followers. Theoretically andpractically, influence and subsequent adoption of innovations is based on sharedvalues and beliefs between opinion leaders and network members. Consequently,opinion leaders must be normatively innovative.

Opinion leaders' access to mass media sources reinforces the "two-step" hypoth-esis of mass media influence an inconsistent with the alternative "hypodermicneedle" hypothesis. As Robinson and Levy (1986) state, "[T]o a large extentinformation does not sink in (or become 'deep processed') until it has been testedand evaluated against the norms and attitudes of one's peers and colleagues" (p.234). This factor makes the importance of understanding interpersonal channelsparamount.

In addition to opinion leaders, there are several other roles evident in the diffusionprocess. These other roles include liaisons (members who link two or more cliqueswithout being members of them), bridges (members who link their own clique toanother clique), isolates (members who are not identified with any particular clique),and cosmopolites (members who provide a connection to nonmembers outside thenetwork; Rogers & Kincaid, 1981). Although we might receive extremely usefulhealth information via mass media and formal, interpersonal sources, it is through aprocess of information exchange and comparison of information to one's culturalnorms that health information can be adopted as part of one's daily practices.

Several studies have used the principles of diffusion of innovations theory toidentify individuals within communities who provide or could provide guidanceregarding health issues (Booth & Babchuck, 1972; Cowen, Gesten, Boike, Norton,Wilson, & DeStefano, 1979; Hays, Catania, McKusick, & Coates, 1990; Howze,Broyden, & Impara, 1992; Kelly, St. Lawrence, Diaz, Stevenson, Hauth, Vrasfield,Kalichman, Smith, & Andrew, 1991; Wiesenfeld & Weis, 1979). Booth and Bab-

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chuck (1972) polled noninstitutionalized adults over the age of 45 to determine theextent and facets of opinion leadership. Their study is an early corroboration of thisphenomenon in health information-seeking. More recent studies by Hays et al.(1990) and Kelly et al. (1991) focusing on AIDS information seeking in gaypopulations indicate that health care deliverers should utilize informal sources (suchas friends, bartenders, and hair stylists) in their emergent roles as confidants andopinion leaders for education, treatment, and sources of information. However,Cowen et al. (1979), Wiesenfeld and Weis (1979), and Howze et al. (1992) all foundthat one-time interventions were not effective beyond the intentional stage ofdecision-making. Howze et al. (1992), for instance, found that while, after two weeks,the clients of a set of hairdressers trained to provide breast cancer and mammogra-phy information indicated behavioral intentions to solicit mammograms, dataacquired a year later indicated no significant treatment effects. As Howze et al.(1992) determined, economic constraints deter socially disadvantaged women fromseeking treatment.

These studies mentioned above indicate that the notion of utilizing informalsources of health information is useful. However, none systematically investigatedthe structure of informal networks as they naturally occur. Additionally, these studiesemphasize authority figures who have considerable influence, as opposed to focus-ing on a network of influence and idea generation. In light of this neglect in previouswork and the implications of diffusion of innovations theory, we posed the followingresearch questions, which guided the portion of the research project discussed onwhich this article focuses:

RQ1: Within a defined informal network, what are the emerging network patterns and roles (i.e.,opinion leaders, liaisons, bridges, isolates) with respect to health-related conversations?

RQ2: Within a defined informal network, what are the characteristics of individuals who areidentified as sources of health information?

Methods

The methodology for in this study was ethnographic and involved participantobservation, personal interviews, and network analysis. The guiding objective was toinvestigate a construct involving health communication rather than a disease andhow communication operated within the group involved. Identifying the partici-pants and designing the specifics of the research project was an emergent processthat entailed two criteria. First, the individuals selected as the focus for the investiga-tion had to interact within a definable network. The intention behind this criterionwas to prevent the number of potential participants from becoming too unwieldy.Second, the members of the network had to gather for purposes other than to discusshealth issues. Our hope was to identify a group for whom health issues were salient,but not necessarily their raison d'etre. This criterion focused on accessing health-conversations that were serendipitous and prosaic.

Participants

A playgroup of "stay-at-home" mothers with infants and toddlers was asked totake part in this study. The routine for these individuals included a weekly playgroupmeeting and a monthly "mom's night out" gathering. The playgroup was one benefitoffered through a community outreach program to integrate "newcomers." Member-

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ship was contingent on having recently moved to the city or having recently becomea mother. The members paid a nominal fee.

There were approximately 30 women involved in the group at any given time;however, only 24 were identified as regular participants for the interviews andsurveys. Characteristically, the women were predominantly "stay-at-home" momswho had given up work or a career (some temporarily). Former occupationsincluded cosmetology, social-services management, computer operations, x-raytechnology, obstetrical nursing, elementary education, and advanced biologicalresearch. The women were all European-American, with two from other countries(Peru and Russia). They ranged in age from 23 to 43. All had at least one child; themaximum was three. Socio-economic status varied from lower class (graduatestudents' wives) to upper middle class (although their specific incomes were un-known). Finally, half of the women were native to the location. The rest hadrelocated because of their husbands' occupations.

While not essentially considered a support group, such as for those coping withaddiction, chronic illness, or terminal illness, this group met with the intention ofproviding connections to new community members. Additionally, while womenhave been giving birth for millennia, they are more reliant than ever on medicaltechnology for what is considered to be a natural process. Indeed, "getting pluggedin" to the network, ultimately gaining support and greater access to institutionalizedhealth services, was one of the primary benefits of this support group.

Procedures

The study occurred in three phases. The initial two consisted of participantobservation and personal interviews with volunteers. The third phase involved asurvey and included a roster to use for network analysis and open-ended questions.

Participant Observation. The members met every week for approximately two totwo and a half hours first, in a church basement, and, then, with the change inseasons, they alternated between a park and a restaurant chain with a playground.The members also met once a month for a "mom's night out." Locations weremembers' homes on two occasions and a restaurant on two others. In all, 14playground meetings and four "mom's night out" meetings were involved.

At the weekly playgroup meetings, the women typically gathered in small groups.They sat or stood, talked with each other, and played with their children. The noiselevel at all of the sites precluded any possibility of audio-taping the interactions. As aresult, the attending researcher sat as unobtrusively as possible near sites of conver-sations and, essentially, "eavesdropped." Notes included information regarding howthe participants gathered, who gathered with whom most often, the tone of conversa-tions, and the content of their interactions. Further, insights and conclusions wereshared with the women to check for differences in perception.

Interviews. In addition to being observed, the participants engaged in personalinterviews designed to solicit narratives with respect to health concerns and ex-amples of information-seeking behaviors. Efforts were made to include a variety ofwomen in terms of age, socio-economic status, and background.

Occurring in the participants' homes at their convenience, the personal interviewslasted a minimum of one hour to a maximum of three hours. All were audio-tapedwith the participants' consent. Thirteen women and one man participated in the

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NETWORK ANALYSIS 343

interviews. The man was included as the husband of one of the participants whohappened to be present during the interview. Questions were of the followingexamples: What health-related issues do you talk about with only a few people?Where do these conversations take place? Can you tell me about a time when whatsomeone said made you seek medical care? What purpose do these conversationsserve for you? All relevant dialogue was subsequently transcribed by the researcherand subjected to inductive analysis.

Survey. The third phase of this study involved a survey that included a roster fromwhich to derive the sociograms and open-ended questions to acquire more informa-tion regarding participants' impressions of health-information seeking. Networkanalysis is a methodology consistent with the theoretical assumptions of diffusion ofinnovations theory and arguments advanced in this study. Historically, networkanalysis has entailed creating sociometric diagrams, "sociograms," in which networkmembers are identified on a chart with lines connecting them to other members ofthe network, and, thereby, revealing their communication patterns. Theoretically,the resulting sociogram can be analyzed in terms of such indices as proximity,connectedness, integration, diversity, and openness, as well as at various levels(Rogers & Kincaid, 1981). The levels of analysis include the individual, the dyad, theclique, and the overall system (Rogers & Kincaid, 1981).

The specific indices selected for this investigation included only proximity andconnectedness. Although there are numerous other variables that could be used todescribe network structures, the small sample size in this study required thislimitation. Proximity is a construct considered fundamental to network analysis(Rogers & Kincaid, 1981). Communicatively, proximity is "the degree to which twoindividuals in a network have personal communication networks that overlap"(Rogers & Kincaid, 1981, p. 149). In terms of links, proximity is the number of directlinks indicating the shortest path between two members. Another index of proximityis the correlational similarity or the degree to which two members are alike in theirpatterns of links and nonlinks.

In addition to proximity, connectedness was evaluated. Defined as "the degree towhich a unit is linked to other units" (Rogers & Kincaid, 1981, p. 181), operationally,connectedness is the number of links between the unit of analysis (individual,cliques, and network) and the other units divided by the number of possible links(which is N-l, when N = the number of units). The larger the clique, the moreunlikely the members are to be strongly connected to each other.

To construct the sociogram, Rogers and Kincaid (1981) recommend asking twofundamental questions: "With whom in this system have you talked most frequentlyabout [topic X]?" (p. 97) and "Do you talk with [person X] daily, about once a week,once a month, once a year, or less often?" (p. 99). Using a matrix of who talks towhom, individuals are arranged in terms of distances and reciprocity of interaction.Sociograms can then convey a sense of opinion leadership, clique membership,isolates, and liaisons.

Constructing sociograms presents some critical difficulties. Essentially a descrip-tive device (Farace, Monge, & Russell, 1977), a major limitation of sociograms is thatare more subjective than objective representations, especially when the populationincreases. The possible number of representations increases exponentially as thenetwork members increase. In line with Albrecht and Ropp's (1982) admonitions,we took the precautions of using multiple means for developing the network

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"picture." In addition to the roster, the open-ended responses and the interviews, aswell as direct, first hand observations of the participants' interactions providedadditional insights in constructing the sociogram. That is, the sociogram developedfrom the responses was checked against the personal knowledge gained fromobservation for clarification.

The open-ended question portion of the survey included the following questions:

Think about people with whom you frequently discuss health issues and explain why you talk withthese persons (this person).What are the characteristics of these persons (this person)?In light of your health-oriented discussions, what is it that you want most?What are "taboo," inappropriate, or difficult health topics to discuss?

The responses were transcribed and coded for analysis. Finally, all the field notes,interview transcripts, and survey responses were coded and analyzed.

Basically, this network analysis of health information-seeking investigated whospoke with whom within the network regarding health issues. Using the rostermethod (Rogers & Kincaid, 1981), the survey we developed for this study involved24 members and requested them to indicate their frequency of interaction regardinghealth issues. First, we created a roster of names from the membership address andtelephone list, with nonattending members (those who had not attended at least oncein the timeframe of the study) omitted and new members added. We used this rosterin the survey requesting the participants to identify the frequency of interaction withthe members regarding health issues.2 The frequencies included never (1), once amonth (2), twice a month (3), once a week (4), two or three times a week (5), and daily(6). Respondents also had the option of "don't know" (i.e., "I don't know who thisperson is") to differentiate between not talking with someone for a variety of reasonsand possibly having a connection with someone, but not being able to identify theperson on die roster. Very often people converse with each other without knowingthe person's name.

As there are few formal rules for developing sociograms (Farace, Monge, &Russell, 1977), Rogers and Kincaid (1981) recommend using software programs,such as NEGOPY (see Richards, 1976, 1986), in combination with smallest-spaceanalysis (multidimensional scaling analysis is another term for smallest-space analy-sis and is used hereafter) to analyze network data and construct a sociogram.NEGOPY may be the best means for assessing the proximity linkages necessary forestablishing network structure. Subsequently, multidimensional scaling (MDS) usescorrelation coefficients of proximity to identify spatially the connection betweenrespondents. Whereas NEGOPY does not print out a sociogram, MDS does.

Once the matrices are determined, they are submitted to (multidimensionalscaling analysis) using SPSS (Diekoff, 1992; Kruskal & Wish, 1976). Similar to clusterand factor analysis, MDS is a descriptive methodology used for initially exploringthe relationship of objects to one another to determine their location along continu-ous dimensions (Diekoff, 1992). In contrast to cluster analysis, MDS is best used fordescribing the proximity or distance of objects, not dieir grouping into types orcategories. As Diekoff (1992) explains:

Multidimensional scaling analysis progresses through three steps or stages. First, proximity dataare generated for all possible pairs of elements being examined. Second, these proximities are usedto map or "scale" the elements into one or more spatial dimensions. Third, the resulting solution isinterpreted, (p. 377)

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Proximity can be determined through both direct and derived measures. Directmeasures include subjective assessments (perceptions), as well as more objectiveassessments, such as observing and recording the frequency of conversation betweentwo employees as a measure of "emotional closeness" (Diekoff, 1992). Derivedproximities involve determining the proximity of objects based on measurementacross a set of descriptor variables. That is, the objects are placed along continuousdimensions according to similar scoring on other variables. There is, reportedly,some discussion regarding whether to use direct or derived proximities, with derivedused more traditionally for cluster analysis and direct for MDS. In this case, the datacollected are direct and, therefore, appropriate for analysis with MDS.

Results

The process of constructing the sociogram is complicated, labor-intensive, andsomewhat arbitrary. However, the emerging picture of the network is verifiable,albeit through an equally subjective process. The results are offered here notnecessarily as a definitive statement, but as a snapshot evaluation of the utility ofnetwork membership. Through network analysis the effectiveness of a support groupcan be determined by identifying individual membership status and linkages.

The intention behind the first research question was to examine the networkstructure of the identified social system. Richards (1986) indicates that, to employNEGOPY, data must be collected from at least 90% of the respondent pool.Unfortunately, in the case of this investigation, that criterion was not satisfied.Instead, the response rate was 62.5% (15 of 24 surveys).3 Thus, Rogers and Kincaid's(1983) recommendations had to be set aside in favor of analyzing the reportedfrequencies by hand in order to produce the network structure. The first step in theanalysis was to construct a matrix of "who talks to whom." Table 1 represents thematrix results, with the letters in bold representative of those members' scores whoresponded to the survey.

This matrix was developed via a comparison of paired responses (for example,participant 11 's response for how often she talks and participant 7's response for howoften #11 talks) to derive a score for each possible dyad. When the responses werereciprocal (for example, both indicated a five), then the score was a five. When theresponses were not reciprocal (for example, a five and a four), then the score waselevated to a five. This decision was made with the consideration that the respon-dents invariably underestimated their level of interaction (since the activity wasrather mundane). If the responses were widely discrepant, the score was determinedby moving each response one step closer and taking the higher of the two responses.In cases in which there was an even middle, dien that number was used. Forexample, if a participant responded with a one and the other with a five, theresponses were elevated and devalued to two and four, respectively. Then, we usedthree as the score, as the median of the two scores. In the case in which a two and fivewere provided as responses, each was elevated to three and four, respectively, widifour as the dyadic score.

Since nine of the 24 participants did not provide information, there were cases forwhich we had only one response. In these circumstances, the response provided wasused as the interaction score. In cases in which the two participants indicated thatthey did not know each other, one was used as the score. Any cell with a "don'tknow" response was scored one. Finally, all empty cells were scored zero. Consid-

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346 COMMUNICATION MONOGRAPHS

Participants

010203040506070809101112131415161718192021222324

0X00040101042201340062310

1 02

X0211211121213211111121

0 3

X011114141411211111111

TABLE

NETWORK MATRIX OF

0 4

X20101011101210012110

0

X1121512312462164314

5 0

X104012101310014310

6 0

X23161312422112111

7 0

X1022201310022110

8 0 9 1

XX

2 11L 13 1

:0

t 1I 5I 5I 0I 0L 3I 3L 3[ 1I 0

1COLUMN 1 AND COLUMN 2

Interaction Scores

01 1

X3414441332251

1 2

X333531133321

1

X04340042210

3 14

X1340021210

1 5 1 6 1 7

X421121121

X41445543

X1155433

18

X021110

! IS

X11110

) 2

X2322

0 2 1

X222

2 2 2 3 2 4

X2 X1 1 X

Bold lettering reflects participants who actually responded.Response rate = 62.5%.

ered ordinal data, these scores were used to determine indices of proximity (usingMDS) and connectedness. Other network indices (e.g., diversity and integratedness)were not determined because of the lack of sufficient data. As stated, Table 1 showsthe matrix results (proximity measures), which were subsequently subjected to MDSanalysis. Table 2 contains the participants' plot symbols and dimensions, as deter-mined through MDS. The analysis began with a determination of coordinates foreach object and situating the coordinates along sets of three, two, and one dimen-sional solutions. Each sociogram was also subjected to a test of "stress" or evaluationof how accurately the derived set of dimensions fit the original data. The mostcommon measure of stress is Kruskal's, which measures "badness of fit." Accordingto Diekoff (1992), "[T]he value of stress increases as the match between proximitiesand mapped distances decreases" (p. 385). A measure of zero indicates a perfect fit,while one indicates a completely imperfect fit.

Although three solutions (three, two, and one) emerged in the output, only thetwo-dimensional solution was applicable to this study. The two-dimensional solutionexhibited a 0.343 stress value and a 0.323 RSQ^value (RSQvalues are the proportionof variance of the scaled data in the partition accounted for by their correspondingdistances).

Figures 2-5 provide the resulting solution or sociogram with the network linksdrawn in succession (as indicated by each title). Bold and CAPITAL lettering de-notes respondents. Examination of these sociograms reveals the network structure(linkages) sequentially, demonstrating the effect of the playgroup meeting. From

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TABLE 2PARTICIPANT IDENTIFICATION AND STIMULUS COORDINATES FOR TWO-DIMENSIONAL SOLUTION

347

Participant

123456789

101112131415161718192021222324

PlotSymbol

aBCdEfGhIjKLMn

opQ.rsTUV

wX

Dimensions

X

0.9490-0.9996-0.81151.07961.21611.1579-1.04090.9784-0.66161.5020-1.04210.4585-0.0682

-0.6714-1.15840.35860.4499

-1.6702-1.6598

0.50741.18781.0153-1.0692

-0.0075

Y

1.3953-1.3512-1.4792

-1.32520.4746

-1.0561-1.0670

-1.1500-1.46350.2466-0.08910.9018-1.00561.4610-0.64230.25590.94890.42070.46820.93300.02050.68270.90831.5117

Figure 2, we see two cliques of women who presumably had contact outside of theplaygroup (since the playgroup met only once a week). Essentially, these women,particularly the largest cluster (L, Q, ,T, a, P, U, E, V), were close friends who con-tacted each other regularly. Their contact included morning walks for exercise,telephone conversations, and face-to-face conversations regarding such topics asdiet, exercise, illnesses, accidents, physician referrals, pregnancy, and breastfeeding.

By observing the changes in the network linkages as demonstrated by Figures 2through 5, the impact is apparent; the lower the level of interaction, the greater thenumber of linkages. However, while the increase of linkages diminishes the sense ofcliques, the identification of key members of the network is increased. A fullerunderstanding of what the sociograms reveal requires some personal informationabout the members gleaned from observation and interviews. A few examples areprovided here to explicate the importance of the network.

P was the chairperson for the playgroup and was the first contact person for newmembers. As such, P served not only as an opinion leader, but also as a bridge.Further, she served as a liaison between the two original cliques. She was a memberof the larger clique, but was also connected with B, who was taking over the role ofchair. L and Q appear to share the exact same coordinates. However, what isinteresting is that these women were actually not close friends. L was only connectedto the clique through P and the playgroup; she was connected to Q, and T at afrequency of twice a month and E only once a month. However, their mutualconnections are numerous, which makes them appear as though they had a highdegree of proximity when, in fact, they were connected rather indirectly.

Members X and J were actively involved in friendships with the larger clique but

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FIGURE 2

TWO-DIMENSIONAL SOLUTION (SOCIOGRAM); FREQUENCY LINKS OF "EVERYDAY"AND " 2 - 3 TIMES A WEEK" [ ] .

could not attend the playgroup because they worked outside the home; however,they did regularly attend the mom's-night-out gatherings. M was the co-chair duringthis study and an opinion leader primarily because of her expertise in obstetricalcare; she was also having a baby at the time of this study and was frequently absentfrom the playgroup. She stated in her survey responses that she enjoyed discussingpregnancy and childrearing and actively sought out people for such discussions.Although she was highly connected to the other members, there was limited accessto her during the course of this study.

In addition to opinion leadership, the role of isolate was important. As thesociograms reveal, there were two particular "pockets" of isolation. B,C, and Iformed one pocket, and h,d, and f formed another. There were particular qualitiesshared by women in these two pockets that made them distinctive. B,C, and I wereisolated primarily because of their international status and unique accents (uniquerelative to the majority of the network members). In essence, these women wereremoved from frequent interaction as a result of cross-cultural barriers. The otherpocket included women who were older than the rest of the other members and whohad a network of friends, separate from the playgroup. Their membership in thisparticular network was precipitated by the birth of their children. That is, while theymaintained contact with their old network, they developed connections to theplaygroup to facilitate care for their child(ren). These women appeared to be less

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NETWORK ANALYSIS 349

FIGURE 3

TWO-DIMENSIONAL SOLUTION (SOCIOGRAM); FREQUENCY LINKS OF " l x A WEEK."

negatively affected by their isolation; rather, they considered their distance to be aproduct of their own choosing. They used the network more for informational needs,whereas the other group of isolates sought out the network in response to bothsocio-emotional and informational needs; sadly, neither was satisfactorily met.

The two-dimensional solution implies that the dimensions or axes have someparticular meaning. While some attempt was made to infer meaning, not enoughdata were collected regarding these women to allow for more than speculation ontheir meanings. It is not clear whether the placement has to do with leadershipqualities, status differences, educational levels, or other factors not directly assessed.Further research that included collecting data on other variables would enhance ourunderstanding.

Despite the problems noted, we still determined the network connectedness bothfor the individuals and the system on the basis of these linkages. Connectedness wasdetermined by dividing each member's number of linkages by the total number ofavailable links (Rogers & Kincaid, 1981), which indicated the degree to which eachmember was linked to the other members. The overall system connectedness wasaffected by including scores for those participants who did not respond. The systemconnectedness was 46.88% when all members were included, and 54.4% when onlyrespondents were included. Table 3 shows the results for the participants' connected-ness. As two separate groups, the respondents' average level of connectedness was56.7%, whereas the nonrespondents' average was 22.8%, which is substantially lower

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350 COMMUNICATION MONOGRAPHS

FIGURE 4

TWO-DIMENSIONAL SOLUTION (SOCIOGRAM); FREQUENCY LINKS OF " 2 X A MONTH."

(more than half). Examination of the sociogram reveals that the nonrespondents areall located on the periphery. Although this positioning does not necessarily distin-guish them from some respondents, it is consistently clear that none of the nonrespon-dents was situated as a key clique member or opinion leader. As such, theseparticipants' lack of response to the survey is consistent with their apparently lowinvolvement level within the network.

These levels of connectedness correspond to the proximity results garnered fromthe MDS analysis. Participants 2, 3, and 9 (B, C, & I) had lower levels of connected-ness, as evidenced through their placement as isolates in the sociogram. Participant16 (P) had the highest level of connectedness, which corresponded to her role as thechairperson for the playgroup. Participants 20 (T) and 11 (K), interestingly, had thesame level of connectedness. Both were considered viable leaders for the playgroup,which leads us to the next research question regarding characteristics of those whomothers seek out for information.

As discussed earlier, on the basis of Rogers's (1983) diffusion of innovations theoryand, more specifically, what he articulates as the characteristics of opinion leaders,influence and subsequent adoption of innovations are based on shared values andbeliefs between opinion leaders and network members. Further, opinion leadersmust be normatively innovative; that is, their decisions to adopt and promote aninnovation are depend directly on the social system's norms regarding change(Rogers, 1983).

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NETWORK ANALYSIS 351

FIGURE 5

TWO-DIMENSIONAL SOLUTION (SOCIOGRAM); FREQUENCY LINKS OF " l x A MONTH.'

The results of this investigation support these claims, in that women who engagedmost in health information-seeking were also avid readers of books, newspapers, andmagazines regarding pregnancy, child rearing, breast feeding, and nutrition. Theyalso relentlessly sought information from new acquaintances, friends, and familymembers regarding not only health care practices, but specific physicians. Addition-ally, participating in the playgroup and gaining the most benefit from the othermothers' experiences required the women to be sociable. Women who did notactively interact with the other mothers during the playgroup gatherings tended tostop attending and, thereby, lost benefits of the network. Finally, the women whohad knowledge or expertise were sought out not only by the network members, butalso by their friends and family members for information. The following interviewexcerpt illustrates the type of information provided:

ER: Do people come to you for information?B: I don't know that they come to me-it's brought up in general topics-general discussions-when

it seems that I have answers that they want.ER: Would they call you up if they had a question?B: Umhmm.ER: Would you direct them to books to read?B: Sometimes, but I have found that most people don't want to read . . . so, you know, one of the

biggest disappointments is when you have a book and you say, this is the best book, why don'tyou read it-and they never do-so I've learned not to lend books.

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352 COMMUNICATION MONOGRAPHS

TABLE 3INDIVIDUAL LEVELS OF CONNECTEDNESS

Participant

aBCdEfGhIjKLMnOP

0.

i-i

sTUVWX

Number of links

9754

145

10866

1613145

14211532

161512105

Connectedness

39%30%21%17%61%22%43%35%26%26%70%57%61%22%61%91%65%13%09%70%65%52%43%22%

N = 24; Bold and CAPITAL lettering denotes respondents.

ER: So, people use you as a filter.B: Yea, I digest all die material and spit out what they need to hear.

In addition to those identified by Freimuth et al. (1989) and Rogers (1983), therewere several other characteristics of people from whom the participants of this studysought general information. Specifically, opinion leaders in this group had children,had breastfed, had same-age children, were approachable, shared similar childrear-ing philosophies, were nonjudgemental, and appeared to have a knowledge of thegeneral topic (had been recommended by someone else). For more personalinformation, such as emotional support or tangible assistance (e.g., Cutrona et al.,1990; House, 1981; House & Kahn, 1985), there were three additional characteris-tics: a close and trusted friend or family member, nonjudgemental and caring, and agood listener. Finally, for specific medical advice, the source of information musthave had experience/training in health care, or must have had the illness or medicalcondition.

One woman, in particular, received calls from other women who had beenreferred to her for information not only about pregnancy and breastfeeding, but alsoconcerning referrals for surgery. While she could recall receiving, on the average,two phone calls a month, during our interview, she received a phone call from awoman seeking information about a cyst the member had had excised and herrecommendations for a hospital and surgeon. In part, this woman was contacted sooften because she was personable and approachable. She was also a recognizedsource of information as she had lived in the community for a lengthy period of timeand was a founding member of the playgroup. Lonely and isolated when she wasnew to the community, she decided to become involved and make contacts. As

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NETWORK ANALYSIS 353

expressed by another playgroup member, the woman was "plugged in" and "is theone I talked to the most-she just seems to know."

In contrast to theory, but certainly appropriate in these circumstances, opinionleadership was based on having direct experience with children. This feature, asrevealed in the surveys and interviews, weighed more heavily than almost any othercredential (i.e., status or education). For example, it was not until the primaryresearcher revealed her own experiences as a mother that her opinion was solicited.Although the members knew that she was well-educated and appeared to beapproachable, it was her stories about childbirth that won their acceptance. Further,a caveat to this feature was whether the mother had similar values to the personseeking information. As such, friends with whom the women had shared thechildbirth experience (i.e., had their babies at the same time) were cited as a majorsource for information.

In addition to pregnancy and childrearing practices, these opinion leadershipcharacteristics applied to other health situations. For instance, when one member'suncle was having problems with his knee and needed surgery, he telephoned hisniece throughout his treatment since she had experienced the same surgery. She wasable to give him details from her experience and reassurances regarding the progressof his recovery and thereby, provide him reassurance as well as information.

Discussion

From this network analysis, we conclude that the emergent network patterns, asindicated by the sociograms, included two basic cliques (L, Q, T, a, V, E,j , U, P & K, W, G) three distinguishable opinion leaders (P, K, M) and two sets ofisolates (B, C, I & h, f, d). The latter did not form a clique as they did not have aconsistent pattern of interaction with each other beyond the playgroup meetings.Members who served liaison and bridge functions included the three opinionleaders, as well as members U, E, Q, f, and h. Members identified as sources ofhealth information evidenced characteristics consistent with Rogers and Kincaid(1981) and Freimuth et al. (1989), with a few additions. Namely, women who hadhad children, breastfed, were approachable, et cetera, were determined to be mostoften accessed. Observations and interviews revealed that sharing one's own story ofchildbirth and childrearing were conducive to establishing homophily (Rogers,1983), credibility, and shared values. Furthermore, being normatively innovativewas essential. For example, one isolate, although knowledgeable about circumci-sion, was continuously rejected by the members. Her views were considered tooradical and her accent too difficult to understand. She was not only denied a place ofleadership, but also reduced to the level of isolate.

The purpose of this study was to examine the structure, content, and impact ofhealth-information seeking in informal, interpersonal networks. In light of diffusionof innovations theory (Rogers, 1983), one goal was to ascertain a means forexamining a heretofore unexplored area, and, thereby, provide an extended pictureof how informal, interpersonal networks enter into the process. Specifically, how is itthat information presented by the "institutions" of medicine, transferred via practi-tioners and mass media, is filtered throughout a social system? Research in our fieldhas focused primarily on two domains, physician-patient interaction and massmediated campaigns, while overlooking and often discounting what occurs on thesocial network level. When considered at all, the focus has been on providing

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354 COMMUNICATION MONOGRAPHS

emotional support (see, for example, Albrecht & Adelman, 1987; Arntson & Droge,1987; Cutrona et al., 1990).

Investigations of this informal sphere have also been conducted from the vantagepoint of how this venue is USEFUL to the institution—going so far as essentially to"plant" informers in a social system (e.g., Cowen et al., 1979; Hays et al., 1990). Todemonstrate the relevance of social networks, investigation must somehow havepractical utility for the health services industry. Perhaps this discriminating standardstems from the inherent nature of health services' focus on saving lives; healthcommunication is inherently "functional." This standard might also stem from thediscipline's continued need to establish legitimacy (Zook, 1994; Zook & Spielvogel,1992). That is, we are seeking to have health care practitioners validate our researchwith their adoption of our concepts and theories. Regardless of the reason for thissituation, the findings of this study can be useful to the industry, to the discipline, andto consumers.

First, health services industries, through managed care and demand managementdirectives, are continually seeking ways to invoke consumers' sense of responsibilityfor appropriate use of available services (e.g., Lengnick-Hall, 1995; Vickery &Lynch, 1995). Furthermore, with insurance providers creating more regulations andstipulations regarding coverage of services, consumers are and will continue to bekey players regarding the practices that enhance and diminish their own healthstatus. Determining how people's health care decisions are influenced by theirinformal network membership can be valuable in two ways:

1. Opinion leadership can be determined and information disseminated through these opinionleaders (who generally have some background and/or experience in the provision andconsumption of health services) to increase network members' access to information deemednot only most accurate, but also most critical.

2. Network structure, roles, and membership can be useful to institutions as they seek torestructure their own organizations either superficially (e.g., their image), or more substantially(e.g., the actual services and quality of services they provide). As these institutions adopt aconsumer-based means for assessing the quality of the product they deliver, knowing mosteffectively how to access consumers should be beneficial.

Second, this research focus can be beneficial to the discipline merely by attempt-ing to outline a means for examining information flow, awareness, influence, anddecision-making as it occurs across a multitude of channels and through numerousparticipants. Typically, we have examined communication regarding health issuesin discrete units while neglecting the system in which "reality" exists. This reality canappear to be so massive and complex that conceptualizing the process seems to beoverwhelming. We have taken apart the various elements, removed them from eachother, and severed a sense of connection each part has with the other. Ironically, ascommunication scholars claiming the processual nature of communication, we haveoverlooked the process in focusing on its components.

The discipline can benefit by utilizing an established, and surprisingly simple,theoretical framework with which to connect the pieces. These networks are ratherlike a critical puzzle piece that makes the rest fall into place. For instance, weunderstand that the institution has been in the making for millennia and has becomean economical and political entity over the last century. Organizationally speaking,the various health, services corporations have been making changes to reduce costs,enhance quality, and increase appropriate access. Mass media ventures have soughtto inform the public of the risks and benefits of various actions. Popular culture has

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NETWORK ANALYSIS 355

served to create an image, albeit flawed and idealistic, that there is indeed anestablished, authoritative position on health issues (see, for example, Turow, 1989).We have laws, regulations, certifications involving health reform in the United Statesand other nations. We understand that the "relationship" between practitioners andconsumers is in evolution and is ideally transforming itself from one of superior-subordinate to a partnership (i.e., Ballard-Reisch, 1990, 1993). But what we have notcomprehended is what happens to directives, recommendations, and edicts tochange health practices once the patient has left the institution and returned to his orher social network. We have not investigated what happens once the "phatic"communication is over (e.g., McKnight, 1988) and the routine practices of lifeobfuscate what seemed reasonable and worthwhile with the practitioner into what ismost culturally acceptable, routine, or simply comfortable.

Neither have we sought to create an overall, systemic interpretation of the flow ofideas into actual practices. This can be done using tools we already have, but in ourattempts to restrict attention to our own pieces, we have lost the "big picture." It is bysharing our knowledge and crossing over artificial disciplinary boundaries that wemight be able to establish a better understanding of why, for instance, people stillsmoke, regardless of evidence that such a practice is lethal, or why people still do notexercise regularly, lower their fat intake, or even drink 8 glasses of water each day,not to mention other important matters, such as seeking prenatal care, havingroutine physical examinations, or taking safer sex precautions, despite tons ofinformation to support these practices. Is it because they do not know, trust, or likedoctors, or is it because they stubbornly refuse to cooperate? Perhaps the answer canbe found by systematically investigating the rest of the process.

Third, there is the question of how this study can benefit consumers. Ideally, that isthe group who might benefit most, but be the least aware of research of the kindreported herein. When those involved in this study became more aware of how theyobtained information and shared it with others, however, they began to talk aboututilizing such a venue more thoughtfully. Their awareness of what they did elevatedthe importance of their roles and conversations. Instead of seeing themselves as"plugged into" the system, they can reframe what they do as being the receptacle,and source of tremendous power. This study comprises an effort to show how the"industry" and the discipline can "plug into" informal, interpersonal networks. Theextent to which such awareness may be empowering and affect ways in whichconsumers interact with others in the medical establishment is a potentially fruitfulavenue for subsequent research.

Endnotes

1 "New" as used here, and especially within the context of this research, does not mean "unknown," althoughthat meaning is encompassed within the definition. An idea, practice, et cetera, can also be considered aninnovation if it is not part of an individual's accustomed routine. For example, it is difficult to imagine a woman,at least within developed countries, who has not heard of mammograms or pap smears, and who has not heardthat women of a certain age or older should undergo regular physical examinations. Hearing about something,though, and adopting that course of action ("innovation") for oneself are distinctly different activities.

2 Each member was asked first to find her own name and circle it. Then, in the first column, they were askedto consider how often they spoke with the listed people about health issues. The second column requested thewomen to consider how often the other person spoke with them.

3 The primary distinction between respondents and nonrespondents can be observed via their placement onthe sociograms (Figures 2-5), as well as their individual levels of connectedness (Table 3).

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