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PRELIMINARY DRAFT

 

Internet paradox:
A social technology that reduces social involvement and psychological well-being?

 

Robert Kraut
Michael Patterson
Vicki Lundmark
Sara Kiesler
Tridas Mukophadhyay
William Scherlis

 

Carnegie Mellon University
June 6, 1998

 

Acknowledgements: This research has been supported by grants from Apple Computer Inc, AT&T Research, Bell Atlantic, Bellcore, CNET, Carnegie Mellon Universityís Information Networking Institute, Intel Corporation, Interval Research Corporation, Hew lett Packard Corporation, Lotus Development Corporation, the Markle Foundation, the National Science Foundation (Grants IRI-9408271 and DSG-9354995), The NPD Group, Nippon Telegraph and Telephone Corporation (NTT), Panasonic Technologies, the U.S. Postal Service, and U S West Advanced Technologies. Farallon Computing and Netscape Communications provided software. Steven Klepper provided valuable statistical advice. We also thank Robert Putnam and Lee Sproull for comments on the manuscript.

 

Abstract

 

The Internet could change the lives of average citizens as much as did the telephone in the early part of the 20th century and television in the 1950s and 1960s. Researchers and social critics are debating whether the Internet is improving or harming p articipation in community life and social relationships. This research examines the social and psychological impact of the Internet on 169 people in 73 households during their first one to two years on-line. We use longitudinal data to examine the effects of the Internet on social involvement and psychological well-being. In this sample, the Internet was used extensively for communication. Nonetheless, greater use of the Internet was associated with declines in participantsí communication with family memb ers in the household, declines in the size of their social circle, and increases in their depression and loneliness. These findings have implications for research, for public policy, and for the design of technology.

 

Introduction

 

Fifteen years ago, computers were mainly the province of science, engineering, and business. By 1998, 43% of all US households owned a personal computer; roughly a third of these homes had access to the Internet. Many scholars, technologists, and socia l critics believe that these changes, and the Internet, in particular, are transforming economic and social life (e.g., Anderson, Bikson, Law, & Mitchell, 1995; Attewell & Rule, 1984; King & Kraemer, 1995). However, analysts disagree as to the nature of these changes, and whether the changes are for better or worse. Some scholars argue that the Internet is causing people to become socially isolated and cut off from genuine social relationships, as they hunker alone over their terminals or comm unicate with anonymous strangers through a socially impoverished medium (e.g., Stoll, 1995; Turkle, 1996). Others argue that the Internet leads to more and better social relationships by freeing people from the constraints of geography or isolation brough t on by stigma, illness, or schedule. According to them, the Internet allows people to join groups on the basis of common interests rather than convenience (e.g., Katz & Aspden, 1997; Rheingold, 1993).

Arguments based on the attributes of the technology alone do not resolve this debate. People can use home computers and the Internet in many different ways and for many purposes, including entertainment, education, information retrieval, and communicat ion. If people use the Internet mainly for communication with others through email, distribution lists, MUDs, and other such applications, they might do so to augment traditional technologies for social contact, expanding their number of friends and reduc ing the difficulty of coordinating interaction with them. On the other hand, these applications disproportionately reduce the costs of communication with geographically distant acquaintances and strangers; as a result, a smaller proportion of peopleís tot al social contacts might be with family and close friends. Other applications on the Internet, particularly the World Wide Web, provide asocial entertainment that could compete with social contact as a way for people to spend their time.

Whether the Internet is increasing or decreasing social involvement could have enormous consequences for society and for peopleís personal well-being. In an influential article, Putnam (1995) documented a broad decline in civic engagement and social pa rticipation in the United States over the past 35 years. Citizens vote less, go to church less, discuss government with their neighbors less, are members of fewer voluntary organizations, have fewer dinner parties, and generally get together less for civi c and social purposes. Putnam argues that this social disengagement is having major consequences for the social fabric and for individual lives. At the societal level, social disengagement is associated with more corrupt, less efficient government and mor e crime. When citizens are involved in civic life, their schools run better, their politicians are more responsive, and their streets are safer. At the individual level, social disengagement is associated with poor quality of life and diminished physical and psychological health. When people have more social contact, they are happier and healthier, physically and mentally (e.g., Cohen & Wills, 1985; Gove & Geerken, 1977).

Although changes in the labor force participation of women and marital breakup may account for some of the declines in social participation and increases in depression since the 1960s, technological change may also play a role. Television, an earlier t echnology similar to the Internet in some respects, may have reduced social participation as it kept people home watching the set. According to Putnam, the diffusion of television into home starting in the 1950 and, more recently, the proliferation of mul tiple sets within a single home led to first to a privatization of entertainment and then to its personalization. One need not arrange a dinner party, join a bridge club, or participate in a bowling league, if curling up alone on the couch with a TV progr am or rented movie is easier and almost as much fun. While television may have been partially responsible for social disengagement (we review some of the evidence on this issue later), technology need not have negative effects on social life. By contrast, other household technologies, in particular, the telephone, are used to enhance social participation, not discourage it (Fischer, 1992). The home computer and the Internet are too new and, until recently, were too thinly diffused into American households to explain social trends that occurred over 35 years, but, now, they could either exacerbate or ameliorate these trends, depending on how they are used.

The goal of this article is to examine these issues and to report early empirical results of a field trial of Internet use. We show that within a diverse sample during their first year or two on-line, participantsí Internet use led to their having, on balance, less social engagement and poorer psychological well-being. We discuss research that will be needed to assess the generality of the effects we have observed and to track down the mechanisms that produce them. We also discuss design and policy imp lications of these results, should they prove stable.

Current debate

Since the introduction of computing into society, scholars and technologists have pondered its possible social impact (e.g., Bell, 1973; Jacobson & Roucek, 1959; Leavitt & Whisler, 1958; Short, Williams, & Christie, 1976). With its rapi d evolution, large numbers of applications, wealth of information sources, and global reach to homes, the Internet has added even more uncertainty. People could use the Internet to further privatize entertainment (as they have purportedly done with televi sion), to obtain previously inaccessible information, to increase their technical skills, and to conduct commercial transactions at homeóeach somewhat asocial functions that would make it easier for people to be alone and to be independent. Alternatively, people could use the Internet for more social purposes, to communicate and socialize with colleagues, friends, and family through electronic mail and to join social groups through distribution lists, newsgroups, and MUDs (Sproull & Faraj, 1995). In t he current section of the paper we draw analogies to earlier technologies as a way to sketching the potential consequences of using the Internet either for entertainment, information, and commerce rather than for interpersonal communication. In the empiri cal section of the paper, we operationalize the distinction between information, entertainment and commerce as compared to interpersonal communication by contrasting the World Wide Web with personal electronic mail, even though we recognize that this oper ationalization is not perfect.. The World Wide Web and electronic mail are by far the most popular of all Internet resources. Electronic mail is typically an exchange of messages between individuals, although, like postal mail and the telephone, it is bei ng increasingly used by corporations and other institutions to broadcast information to many, undifferentiated consumers. In comparison, the Web is more like broadcast mediaóbillboards, magazines, radio, and televisionóalthough on the Web, almost anyone c an publish.

Internet for entertainment, information, and commerce. If people use the Internet primarily for entertainment and information, the Internetís social effects might resemble those of television. Most research on the social impact of television has focused on its content; this research has investigated the effects of TV violence, educational content, gender stereotypes, racial stereotypes, advertising, and portrayals of family life, among other topics (Huston et al, 1992). Some social critics have argued that television reinforces sociability and social bonds (McLuhan, 1964, p. 304; Beninger, 1987, pp. 356-362). One study comparing Australian towns before and after television became available suggests that the arrival of television led to increases in social activity (Murray & Kippax, 1978). However most empirical work has indicated that television watching reduces social involvement (Brody, 1990; Jackson-Beeck & Robinson, 1981; Neuman, 1991; Maccoby, 1951). Recent epidemiological research has linked television watching with reduced physical activity and diminished physical and mental health (Andersen et al, 1998; Sidney, Sternfeld, Haskell, Jacobs, Chesney, & Hulley, 1998).

If watching television does indeed lead to a decline in social participation and psychological well-being, the most plausible explanation faults time displacement. That is, the time people spend watching TV is time they are not actively socially engage d. Basing their estimates on detailed time dairies, Robinson and Godbey (1997; see also Robinson, 1990) reported that a typical American adult spends three hours each day watching TV;; consuming 40% of the typical Americanís free time; childrenís TV watch ing is much higher (Condry, 1993). Although a large percentage of TV watching occurs in the presence of others, the quality of social interaction among TV viewers is low. People who report they are energetic and happy when they are engaged in active socia l interaction also report they are bored and unhappy when they are watching TV (Kuby & Czikzenmihly, 1990). Lonely people report using TV more than others (Canary & Spitzberg, 1993) and people report using TV to alleviate loneliness (Rubinstein &a; mp; Shaver, 1982; Rook & Peplau, 1982). Although we cannot disentangle the direction of causation in this cross-sectional research, a plausible hypothesis is that watching TV causes both social disengagement and worsening of mood.

Like watching television, using a home computer and the Internet generally imply physical inactivity and limited face-to-face social interaction. Some studies, including our own, have indicated that using a home computer and the Internet can lead to in creased skills and confidence with computers (Lundmark et al., 1998). However, if people use these technologies intensively for learning new software, playing computer games, or retrieving electronic information, they may find these activities to be time consuming and to lead to more time spent alone (Vitalari, Venkatesh, & Gronhaug, 1985). Some cross-sectional research suggests that home computing may be displacing television watching itself (Danko & McLachlan,1983; Kohut,1994) as well as reducin g leisure time with the family (Vitalari, Venkatesh, & Gronhaug, 1985).

Internet for interpersonal communication. The Internet, like its network predecessors (Sproull & Kiesler, 1991), has turned out to be far more social than television, and in this respect, the impact of the Internet may be more like that of t he telephone. Over the Internet, people can communicate with family, with friends and with relative strangers using personal electronic mail. Using group distributions lists, such as Listservs, public bulletin boards, such as Usenet news groups, or real-t ime communication services, such as MUDs or chats, they have conversations with large numbers of people simultaneously, many of whom they do not know individually, or eavesdrop on the public conversations of others. Our research has shown that interperson al communication is the dominant use of the Internet at home (Kraut, Mukhopadhyay, Szczypula, Kiesler, & Scherlis, 1998). A sample of teenagers and adults, observed over the course of 12 months, used personal electronic mail more frequently than they used the World Wide Web and, when they logged on to the Internet, they accessed electronic mail before they accessed the World Wide Web. Their use of electronic mail was more stable over time than their use of the World Wide Web, and heavy use of electron ic mail led to their increasing their use of the Internet more in subsequent sessions, whereas heavy use of the World Wide Web led them to reduce their subsequent use of the Internet. That people use the Internet mainly for interpersonal communication, ho wever, does not imply that their social interactions and relationships on the Internet are the same as their traditional social interactions and relationships (Sproull & Kiesler, 1991), or that their social uses of the Internet will have effects compa rable to traditional social activity.

Whether social uses of the Internet have positive or negative effects may depend on how the Internet shapes the balance of strong and weak network ties that people maintain. Strong ties are relationships associated with frequent contact, deep feelings of affection and obligation, and application to a broad content domain whereas weak ties are relationships with superficial and easily broken bonds, infrequent contact, and narrow focus. Strong and weak ties alike provide people with social support. Weak ties (Granovetter, 1973), including weak on-line ties (Constant, Sproull, & Kiesler, 1996), are especially useful for linking people to information and social resources unavailable in peopleís closest, local groups. Nonetheless, strong social ties are the relationships that generally buffer people from lifeís stresses and that lead to better social and psychological outcomes (Cohen & Wills, 1985; Krackhardt, 1994). People receive most of their social support from people with whom they are in most frequent contact, and bigger favors come from those with stronger ties (Wellman & Wortley, 1990). The major exceptions to this generalization are (1) that strong social ties tend to be redundant, especially for informational resources (Burt, holes) an d (2) that the marriage tie for women but not for men may increase stress more than it increases social support (Gove. & Geerken, 1977).

Generally, strong personal ties are supported by physical proximity.Once strong ties are established through any route, they can be and frequently are sustained using telecommunications (Wellman & Tindall, 1993). The Internet potentially reduces th e importance of physical proximity in creating and maintaining networks of strong social ties. Unlike face-to-face interaction or even the telephone, the Internet offers opportunities for social interaction that do not depend on the distance between parti es. People often use the Internet to keep up with those to those with whom they have pre-existing relationships (Kraut et al, 1998). But they also develop new relationships on-line. Most of these new relationships are weak. MUDs, listservs, newsgroups, an d chat rooms put people in contact with a pool of new groups, but these on-line "mixers" are typically organized around specific topics, activities, or demographics, and rarely revolve around local community and close family and friends.

Whether a typical relationship developed on-line becomes as strong as a typical traditional relationship and whether having on-line relationships changes the number or quality of a personís total social involvement are open questions. Empirical evidenc e about the impact of the Internet on relationships and social involvement is sparse. Many authors have debated whether the Internet will promote community or undercut it (e.g., Rheingold, 1993; Stoll, 1995; Turkle, 1996) and whether personal relationship s that are formed on-line are impersonal or as close and substantial as those sustained through face-to-face interaction (Berry, 1993; Heim, 1992; Walther, Anderson, & Park, 1994). Much of this discussion has been speculative and anecdotal, or is base d on cross-sectional data with small samples.

Current data

Katz and Aspdenís national survey (1997) is one of the few empirical surveys that has compared the social participation of Internet users with non-users. Controlling statistically for education, race, and other demographic variables, these research ers found no differences between Internet usersí and nonusersí memberships in religious, leisure, and community organizations and in the amount of time users and non-users reported spending communicating with family and friends. From these data Katz and A spden concluded that " [f]ar from creating a nation of strangers, the Internet is creating a nation richer in friendships and social relationships" (p. 86).

 

Katz and Aspdenís conclusions may be premature because they used potentially inaccurate, self-report measures of Internet usage and social participation that are probably too insensitive to detect gradual changes over time. Furthermore, their observati on that people have friendships on-line does not necessarily lead to the inference that using the Internet increases peopleís social participation or psychological well-being; to draw such a conclusion, one needs to know more about the quality of their on -line relationships and the impact on their off-line relationships. Many studies show unequivocally that people can and do form on-line social relationships (e.g., Parks & Floyd, 1995). Katz and Aspdenís first class of evidenceó failure to find reliab le differences between Internet users and non-user on measures of organizational membership and time spent with family and friendsóis compromised by insensitive self-report measures of both Internet usage and social participation. Respondents to their nat ional survey classified themselves as current Internet users, former Internet users, or non-users. The users were subdivided into "longtime Internet users" or not. This classification makes no differentiation between people who use the Internet to differe nt degrees or for different purposes. Thus, the 30-minute per week and 3-hour per day user are treated equally. Their measures of social participation are similarly insensitive. Respondents in the survey reported on their membership in organizations rathe r than on behavioral measures of involvement or participation. If use of the Internet leads to a ten-percent change in church attendance or volunteering for community organizations, Katz and Aspdenís measures would not picked this up. In drawing conclusio ns on social communication, Katz and Aspden asked respondents to report on changes in the time they spent with family and friends face-to-face or by phone since starting to use the Internet Self-reports of time use are notoriously inaccurate (Robinson &am; p; Godbey, 1996) and respondents are especially poor as assessing change (Bem and McConnell, 1970). As a result, self-reported change scores, which require respondents to perform mental arithmetic on estimates that are themselves likely to be inaccurately remembered, are likely to be filled with error. and Aspdenís second class of evidenceóthe observation that people use the Internet to keep up with families and to make friendsófails to include any comparison between Internet users and non-users. A substa ntial number of studies now show unequivocally that people can and do form on-line social relationships. Kraut et al (1998) demonstrated that interpersonal communication was the dominant motive for peopleís continued use of the Internet. Par ks and Floyd (1995) showed that about 60% of a sample of people who post to Internet newsgroups formed new personal relationships as a result of their participation in the newsgroup, with half communicating with their on-line partner at least weekly. Katz and Aspden (1997) note that Internet subscribers use it to contact family members and to form friendships, with the formation of on-line friendships increasing with usersí on-line experience. However, these data do not speak to the frequency, depth, and impact of on-line relationships compared with traditional ones or whether the existence of on-line relationships changes traditional relationships or the balance of peopleís strong and weak ties.

Even if a a cross-sectional survey were to convincingly demonstrate that Internet use is associated with greater social involvement, it would not establish the causal direction of this relationship. In many cases, it is as plausible to assume that soci al involvement causes Internet use as the reverse. For example, many people buy a home computer to keep in touch with children in college or with retired parents. People who use the Internet differ substantially from those who do not in their demographics , skills, values, and attitudes. Statistical tests often under-control for the influence of these factors, which in turn can be associated with social involvement (Anderson et al, 1995; Kraut et al, 1996; Times-Mirror, 1994). Because statistical test typi cally under-control for the influence of these factors, cross-sectional studies cannot eliminate the possibility that a factor such as higher education may be driving community involvement and use of the Internet.

A longitudinal study of Internet use

The research described here examines the causal relationship between peopleís use of the Internet, their social involvement, and certain likely psychological consequences of social involvement using longitudinal data. The data come from a field tri al of Internet use, in which we tracked the behavior of 169 participants over their first one or two years of Internet use. It improves on earlier research by using accurate measures of Internet use and a panel research design. Measures of Internet use we re recorded automatically, and measures of social involvement and psychological well-being were collected twice, using reliable self-report scales and distinguishes use of the Internet for communication (personal email) from use of the Internet to access information and entertainment (World Wide Web). Because we tracked people over time, we can observe sequential change, and control statistically for social involvement, psychological states, and demographic attributes of the trial participants that existe d prior to their use of the Internet. With these statistical controls and measures of change, we can draw stronger causal conclusions than is possible in research in which the data are collected once.

 

Method

Sample

The HomeNet study consists of a sample of 93 families from eight diverse neighborhoods in Pittsburgh. People in these families began using a computer and the Internet at home either in March, 1995 or March, 1996. Within these 93 families, 256 membe rs signed consent forms, were given email accounts on the Internet, and logged on at least once. Children younger than 10, and uninterested members of the household are not in the sample.

Each yearís subsample was drawn from four school or neighborhood groups so that the participants would have some pre-existing communication and information interests in common. The first yearís participants consisted of families with teenagers particip ating in journalism classes in four area high schools. The second yearís participants consisted of families in which an adult was on the board of directors of one of four community development organizations. The community activists were not required to ha ve a second family member join the study but nearly all of them did.

Families received a computer and software, a free extra telephone line and free access to the Internet in exchange for permitting the researchers to automatically track their Internet usage and services, for answering periodic mail questionnaires, and for agreeing to an in-home interview. The equipment provided to participant households included Macintosh computers with modems and software installed for ready Internet access. The families used Carnegie Mellon Universityís proprietary software for elect ronic mail, MacMail II, Netscape Navigator for web browsing, and ClarisWorks Office. At least two family members also received a morningís training in the use of the computer, email, and the Web.

None of the groups approached about the study declined the invitation, and over 90% of the families contacted within each group agreed to participate. Because the recruitment plan excluded households or individuals with active Internet connections, the data represent people's first experiences with Internet use, and for all but a few of the households, their first experience with a powerful home computer.

Some participants left the study to attend college, because they moved, or for other reasons. Of the 256 individuals who completed the pretest questionnaire, 169 (66%) from 73 household also completed the follow-up questionnaire. Table 1 provides descr iptive statistics on the sample that completed both a pretest and posttest questionnaire. Compared with participants who completed only the pretest questionnaire, participants who completed both were wealthier ($53,300 versus $43,600 household income, r=. 20, p < 01), more likely to be adults (74% versus 55%, r = .16, p < .01), and less lonely (1.98 versus 2.20 on a 5-point scale, r=-.13, p < .05). They did not differ on other measures.

Because estimates of communication within the family were based on reports from multiple family members, we have data for 231 individuals for this measure.

Data collection

We measured demographic characteristics, social involvement, and psychological well-being of participants in the HomeNet trial on a pretest questionnaire before the participants were given access to the Internet. After 12 to 24 months, participants completed a follow-up questionnaire containing the measures of social involvement and psychological well-being. During this interval, we automatically recorded their Internet usage using custom-designed logging programs. The data reported here encompass the first 104 weeks after a HomeNet familyís Internet account was first operational for the 1995 subsample and 52 weeks of use from the 1996 subsample.

Demographic and control variables. In previous analyses of this sample, we found that the demographic factors of age, gender, and race were associated empirically with Internet usage (Kraut et al., 1998). Others have reported that household inco me is associated with Internet usage (Anderson, Bikson, Law, & Mitchell, 1995). We used those demographic factors as control variables in our equations. Also, as a control variable that might influence participantsí family communication, social networ k, social support, and loneliness, we included in those analyses a measure of social extraversion (e.g., "I like to mix socially with people," Bendig, 1962). A few other controls used in single analyses are described below.

Internet usage. Software recorded the total hours in a week in which a participant logged into the Internet. Electronic mail and the World Wide Web were the major applications that participants used on the Internet and account for most of their time on-line. Internet hours also included time that participants read distribution lists such as Listservs, or Usenet newsgroups, and participated in real-time communication using Web chat lines, MUDs, and Internet Relay Chat. For the analyses we report here, we averaged weekly Internet hours over the period in which each participant had access to the Internet, from the pretest up to the time he or she completed the follow-up questionnaire. Our analyses use the log of the variable to normalize the distri bution.

Personal electronic mail use: We recorded the number of email messages participants sent and received. To better distinguish the use of the Internet for interpersonal communication rather than information and entertainment, we excluded email mes sages in which the participant was not explicitly named as a recipient in our count of received mail. These messages typically had been broadcast to a distribution list to which the participant had subscribed. We believe these messages reflect a mix of in terpersonal communication and information distribution.

World Wide Web use: We recorded the number of unique World Wide Web domains or sites accessed visited per week (a domain or site is an Internet protocol address, such as www.disney.com). Our metric for total volume of World Wide Web use is the n umber of different domains accessed during the week. The average number of weekly domains visited and the average number of weekly html pages retrieved were very highly correlated (r=.96).

Social involvement and psychological well-being. Before participants gained access to the Internet and (depending on sample) approximately 12 to 24 months later, they completed questionnaires assessing their social involvement and psychological well being. We used four measures of social involvement: family communication, size of local social network, size of distant social network, and social support. To measure family communication, we asked participants to list all the members of their household and to estimate the number of minutes they spent each day communicating with each member. Pairs reported similar estimates (r = .73) and their estimates were summed. The total amount of family communication for each partici pant is the sum of the minutes communicating with other family members. Extreme values (greater than 400 minutes) were truncated to 400 minutes. Because the measure was skewed, we took its log in the analyses that follow, to make their distributions more normal. Family communication is partly determined by the number of family members and is interdependent within households, so we controlled statistically for these group effects by including family as a dummy variable in the analyses involving family comm unication.

To measure the size of participantsí local social network, we asked them to estimate the "the number of people in the Pittsburgh area... whom you socialize with at least once a month." The size of their distant social network was defined as "the number of people outside of the Pittsburgh area whom you seek out to talk with or to visit at least once a year." Because both measures had some outliers, they were truncated (at 60 for the local circle and 100 for the distant circle); because they were skewed, we took their log in the analyses that follow.

Social support is a self-report measure of social resources that theoretically derives from the social network. To measure participantsí levels of social support, we asked them to complete 16 items from Cohen et alís (1984) social support scale (Cronba chís alpha = .80), which asks people to report how easy it is to get tangible help, advice, emotional support, and companionship, and how much they get a sense of belonging from people around them (e.g., "There is someone I could turn to for advice about changing my job or finding a new one").

We used three measures of psychological well-being that have been associated with social involvement: loneliness, stress, and depression. Participants completed 3 items (Cronbachís alpha = .54) from the UCLA Loneliness Scale (versi on 2), which asks people about their feelings of connection to others around them (e.g., "I canít find companionship when I want it," (Russell et al., 1980). To measure stress we used a proxy, number of stressors in oneís life. Participants reported wheth er they experienced one or more of 49 possible daily life stressors in the preceding month; the stressors ranged from having oneís car break down, to not liking school, to illness in the family (Kanner et al, 1981). Because stress is often a trigger for d epression, this measure also was included as a control variable in analyses involving depression. Participants completed 15 items from the CES-D scale (Cronbachís alpha = .86) measuring depression in the general population. The scale asks respondents to r eport feelings, thoughts, symptoms, and energy levels associated with mild depression (e.g., "I felt that everything I did was an effort," "I felt I could not shake off the blues, even with help from family and friends," Radloff, 1977).

Analysis

Our data analysis examines how changes in peoplesí use of the Internet over 12 to 24 months was associated with changes in their social involvement and psychological well-being. We statistically controlled their initial levels of social involvement and psychological well-being, as well as certain demographic and control variables. Figure 1 describes the logic of our analysis as a path model (Bentler, 1995).

Figure 1: Logic of social impact analyses

We used path analysis to test the relationships among variables measured at three time periods: pretest questionnaire at T1, Internet usage during T2, posttest questionnaire at T3. The statistical associations among demographic characteristics, social involvement, and psychological well-being measured at T1 and Internet use measured at T2 provide an estimate of how much pre-existing personal characteristics led people to use the Internet. The link between social involvement and psychological well-being at T1 and at T3 reflects stability in involvement and well-being. Evidence that using the Internet changes social involvement and psychological well-being comes from the link between Internet use at T2 and social involvement and psychological well-being at T3. Since this analysis controls for a participantsí demographic characteristics and the initial level of the outcome variables, one can interpret the coefficients associated with the link between Internet use at T2 and outcomes at T3 as the effect of Internet use on changes in social involvement and psychological well-being (Cohen & Cohen, 1983). By using longitudinal data, measuring Internet use over an extended period and measuring the outcome variables at two time periods, we can evaluate the p ossibility that initial social involvement or psychological well-being led to Internet use. We explicitly test this possibility in the link between involvement and well-being at T1 and Internet use at T2; this link is controlled when we test the Internet use at T2 to outcome link at T3.

Results

Table 1 presents the means and standard deviations of the demographic variables, measures of Internet use, social involvement, and psychological well-being used in this study. Table 2 presents a correlation matrix showing the relationships among th ese variables.

Table 1: Description of the sample.

Variable

N
Mean
Std

Household income (dollars in thousands)

164

54.46

22.79

Race (white = 1, minority = 0)

167

.75

.43

Age (teen = 1, adult = 0)

169

.28

.45

Gender (female = 1, male = 0)

169

.56

.50

Social extraversion (1-5-point scale)

169

3.66

.80

Household size (individuals in household at pretest)

231

4.08

1.02

Family communication T1 (mean hours per day)

231

4.29

2.67

Family communication T3 (mean hours per day)

231

4.51

2.65

Local social network T1 (number of people)

166

23.94

17.87

Local social network T3 (number of people)

166

22.90

16.58

Distant social network T1 (number of people)

166

25.43

27.30

Distant social network T3 (number of people)

166

31.73

31.04

Social support T1 (1-5-point scale, 16 items)

164

3.97

.51

Social support T3 (1-5-point scale, 16 items)

166

3.97

.56

Loneliness T1 (1-5-point scale, 3 items)

165

1.99

.71

Loneliness T3 (1-5-point scale, 3 items)

163

1.89

.73

Stress T1 (mean of hassles reported of 49 items)

169

.23

.15

Stress T3 (mean of hassles reported of 49 items)

169

.23

.17

Depression T1 (0-3 scale, 15 items)

167

.73

.49

Depression T3 (0-3 scale, 15 items)

164

.62

.46

Internet usage T2 (mean hours per week)

169

2.43

4.94

 

Note. The units of the means and standard deviations for Internet hours and family communication are weekly hours.

Table 2: Correlations among variables.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

18

19

20

1

Household income (dollars in thousands)

2

Race (white = 1, minority = 0)

.28

3

Age (teen = 1, adult = 0)

-.03

.08

4

Gender (female = 1, male = 0)

-.14

-.20

.03

5

Social extraversion (1-5-point scale)

.11

.00

.12

.19

6

Household size (people in household at pretest)

.27

.16

.16

-.07

.17

7

Family communication T1(mean hours per day)

-.14

-.01

-.07

.18

.09

.28

8

Family communication T3 (mean hours per day)

-.03

-.10

-.28

.14

-.09

.01

.40

9

Local social network T1 (number of people)

-.05

-.02

.27

.03

.07

.13

.09

.01

10

Local social network T3 (number of people)

-.06

-.02

.24

.04

.12

.17

.20

.01

.56

11

Distant social network T1 (number of people)

.14

.14

.02

.02

.06

.00

.09

.01

.30

.17

12

Distant social network T3 (number of people)

.18

.27

.16

-.17

.06

.07

.06

.03

.16

.36

.38

13

Social support T1 (1-5-point scale, 16 items)

.12

.05

.05

.22

.34

.04

.25

.05

.16

.08

.06

.10

14

Social support T3 (1-5-point scale, 16 items)

.14

.13

.05

.18

.30

.14

.12

.04

.10

.14

.19

.13

.57

15

Loneliness T1 (1-5-point scale, 3 items)

-.09

-.07

-.18

-.08

-.37

-.12

-.25

-.10

-.21

-.19

-.08

-.18

-.61

-.48

16

Loneliness T3 (1-5-point scale, 3 items)

.07

-.08

-.05

-.21

-.36

-.07

-.15

-.05

-.30

-.23

-.15

-.12

-.49

-.67

.55

17

Stress T1 (mean of hassles reported of 49 items)

-.01

-.01

-.15

.09

.04

.07

.06

.10

.03

.00

.07

-.09

-.08

-.01

.13

.09

18

Stress T3 (mean of hassles reported of 49 items)

-.02

.13

.01

.05

.01

-.01

-.05

-.03

.07

.06

.00

.08

-.09

.10

.05

.01

.60

19

Depression T1 (0-3 scale, 15 items)

.07

.05

.33

.10

-.14

.14

-.07

.03

.16

.12

.04

.08

-.26

-.12

.22

.24

.37

.30

20

Depression T3 (0-3 scale, 15 items)

-.07

-.15

.14

.03

.00

-.06

-.08

-.20

-.07

-.06

-.13

-.11

-.12

-.36

.25

.36

.21

.31

.32

21

Internet usage T2 (mean hours per week)

.06

.17

.23

-.07

-.10

-.07

-.09

-.08

-.07

-.11

-.08

-.05

-.01

-.04

-.09

.15

-.14

.04

.07

.15

 

Note. N for household size and family communication = 231. Other Ns vary between 163-169. Family communication, social networks, and Internet use have been logged before computing correlations.

When r =.15, p =.05; when r=.17,p=.025;when r=. 20, p=.01.

 

All the path models are summarized in Table 3. When these models are complex, we also show these relationships graphically, in Figures 2-4.

Social involvement

Family communication. Figure 2 documents a path model in which the amount of time participants communicated with other members of their households is the dependent variable. Coefficients in the model are standardized beta weights showing the relati onships among variables linked by arrows, when variables measured earlier have been controlled. Because communication within a single household is interdependent, we included a dummy variable for each family in the analysis. For purposes of clarity, only links with coefficients significant at the .05 level or less are included in Figure 2, although the full set of coefficients is included in Model 1 in Table 3.

The analysis of family communication shows that teenagers used the Internet more hours (T2) than did adults, but whites did not differ from minorities and females did not differ from males in their average hours of use. Different families varied in the ir use of the Internet (the family dummy variable), but the amount of communication that an individual family member had with other members of the family did not predict subsequent Internet use. Family communication was stable over the period from T1 to T 3. Whites increased their family communication more than minorities did. Adults increased their communiction more than teens, and females increased their communication in the family more than males did. For our purposes, the most important finding is that greater use of the Internet was associated with subsequent declines in family communication.

 

Figure 2: Influence of Internet use on family communication
Note: Entries are standardized beta coefficients. All paths are significant p <= .05. a. Family was represented by 72 dummy variables differrentiating the unique families, and therefore doesn't have a single estimate.

 

 

 

Table 3. Effects of the Internet on social involvement and psychological well-being.

Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Model 7

Internet hours
Family commun-ication T3
Internet hours
Local social circle T3
Internet hours
Distant social circle T3
Internet hours
Social support T3
Internet hours
Loneliness T3
Internet hours
Stress T3
Internet hours
Depression T3

Intercept

.00

.00

-.03

-.01

-.03

-.01

-.02

.00

.02

.00

-.01

-.01

.03

Household income (dollars in thousands)

.05

-.01

.06

.08

.04

.07

.04

.13

Ü

.02

-.06

-.01

-.04

Race (white = 1, minority = 0)

.02

.10

.14

.03

.16

Ü

.19

.12

.11

.12

-.16

*

.15

.11

.12

-.21

*

Age (teen = 1, adult = 0)

.18

**

-.09

*

.25

**

.10

.21

**

.13

Ü

.23

**

.00

.20

**

.02

.18

*

.07

.15

.09

Gender (female = 1, male = 0)

-.01

.09

*

.01

.06

.02

-.11

-.01

.07

.00

-.14

*

-.01

.01

-.02

-.03

Social extraversion (5-point scale)

-.16

*

.03

-.16

*

-.03

-.18

*

.09

-.20

-.16

*

Familya

***

Family communication T1 (mean hours/ day

.40

***

Local social circle T1 (number of people)

-.14

Ü

.53

***

Distant social circle T1 (number of people)

-.12

.33

***

Social support T1 (5-point scale, 16 items)

.04

.51

***

.01

-.03

Loneliness T1 (5-point scale, 3 items)

-.11

.50

***

Stress T1 (mean of hassles reported of 49 items)

-.11

.65

***

-.13

.17

Ü

Depression T1 (0 ñ 3 scale, 15 items)

.22

*

Internet usage (mean hours per week)

-.08

*

-.14

*

-.14

Ü

-.05

.15

*

.11

Ü

.19

*

R Square

.42

.84

.10

.34

.10

.09

.09

.35

.10

.38

.08

.41

.07

.19

N

231

231

158

155

158

156

156

152

157

152

161

161

155

150

 

NOTE: Ü P< .10, * P < .05, ** P < .01, *** P < .001
aFamily was represented by 72 dummy variables differentiating the unique families, and therefore does not have a single estimate.

 

Size of participantsí social networks. Models 2 and 3 in Table 3 present analyses involving the size of participantsí local and distant social circles, respectively. Because social extroversion may influence the number of friendships that an individual maintains and because preliminary analyses showed that more extroverted individuals subsequently used the Internet less, we included social extroversion as a control variable.

Greater social extroversion and having a larger local social circle predicted less use of the Internet during the next 12 or 24 months. Whites reported increasing their distant social circles more than minorities did and teens reported increasing their distant circles more than adults did; these groups did not differ in changes to their local circles. Holding constant these control variables and the initial sizes of participantsí social circles, greater use of the Internet was associated with subsequen t declines in the size of both the local social circle (p < . 05) and, marginally, the size of the distant social circle (p < . 07).

Social support. The social circle measures ask respondents to estimate the number of people with whom they can exchange social resources. However, the definition provided to participants may have focused their attention primarily on people with whom they had face-to-face contact, thus leading to a biased view of social resources if the Internet allowed for the substitution of on-line contacts for face-to-face ones. The social support and loneliness measures are more direct measures of the conseq uences of having social contact and are not inherently biased by the medium of communication.

The social support measure and the loneliness measure have some items with comparable content (e.g., "I can find companionship when I want it" is on the loneliness scale and "When I feel lonely, these are several people I can talk to" is on the social support scale. Also, the two measures are correlated (r = .60). However, whereas the loneliness scale focuses on psychological feelings of belonging, the social support scale includes components measuring the availability of tangible resources from others (e.g., a loan), intangible resources from others (e.g., advice), and reflected esteem (e.g., repect for abilities).

Model 4 in Table 3 is a path analysis in which social support was the dependent variable. We included the extroversion scale at T1 as a covariate. Because we were able to distinguish differential associations of using the World Wide Web and email on so cial connection, we have substituted them for average hours of Internet use in Model 2. altyAlthough Although the association between Internet use and subsequent social support is negative, the effect does not approach statistical significance (p & gt;. 40).

Household communication.

Loneliness. Model 5 in Table 3 is the path analysis involving the loneliness scale. We included the extroversion scale at T1 as a covariate. Because we were able to distinguish differential associations of using the World Wide Web and email on social connection, we have substituted them for average hours of Internet use in Model 2. Figure 3 summarizes the results. Note that initial loneliness does not predict subsequent Internet use. Loneliness was stable over time. People from richer househ olds increased loneliness more than those from poorer households did, men increased loneliness more than did women, and minorities increased loneliness more than did whites. Controlling for these personal characteristics and initial loneliness, people who used the Internet more subsequently reported larger increases in loneliness. The association of Internet use with subsequent loneliness was comparable to the associations of income, gender, and race with subsequent loneliness.

.

Figure 3: Influence of Internet use on loneliness.
Note: Entries are standardized beta coefficients. All paths were significant p < = .05.

 

 

Stress. Model 6 in Table 3 describes the analysis involving self reports of daily "hassles," an index of the extent of daily life stress. The occurrence of these stressors was stable over the interval we studied. People who used the Internet mor e reported experiencing a greater number of daily life stressors in a subsequent period, an increase that is marginally significant (p =. 08). The Hassle Scale is a simple mean of a large number of stressors. We tried to gain more insight into the detailed changes that were occurring in participantsí lives by conducting an exploratory, post-hoc analysis to identify the particular stressors that increased with Internet use. We conducted separate analysis for each potential stressor, regressing it on its occurence at the pretest time and the other variables from Model 6., and we used the Bonferroni correction to guard against capitalizing on chance in reporting results. Under this analysis, no single stressor changed reliably from its baseline. The i mplication is that while use of the Internet may increase aggregate stress, it does not do so through a common route across the sample.

Depression. Model 7 in Table 3 presents the path analysis involving depression; Figure 4 shows the significant variables. Because stress often triggers depression and social support is often a buffer protecting against depression, we included bo th the hassle and social support measures at T1 as covariates. Because we were able to distinguish differential associations of using the World Wide Web and email on social connection, we have substituted them for average hours of Internet use in Model 2. The stability of depression in this sample was lower than the stability of other outcomes measured, but was comparable to its stability in other general populations (Radloff, 1977). Initial depression did not predict subsequent Internet use. Minorities r eported more increases in depression than whites and those with higher initial stress also reported greater increases in depression. For the purposes of this analysis, the important finding is that greater use of the Internet was associated with increased depression at a subsequent period, even holding constant initial depression and demographic, stress, and support variables that are often associated with depression. This negative association between Internet use and depression is consistent with the int erpretation that use of the Internet caused an increase in depression. Again, it is noteworthy that depression at T1 did not predict using the Internet subsequently.

Figure 4: Influence of Internet use on depression.
Note: Entries are standardized beta coefficients. All paths are significant p <= .07.

 

Discussion

Evaluating the causal claim

The findings of this research provide a surprisingly consistent picture of the consequences of using the Internet. Greater use of the Internet was associated with statistically significant declines in social involvement as measured by communication within the family and the size of peopleís local social networks, and with increases in loneliness, a psychological state associated with social involvement. In terms of social involvement, greater use of the Internet is associated with a declines in siz e of the social circle, declines in social contact, and declines in family communication. Greater use of the Internet also was associated with increases in depression. Other effects on size of the distant social circle, social support, and stress did not reach standard significance levels but the observed effects were consistently negative.

Our analyses are consistent with the hypothesis that using the Internet adversely affects social involvement and psychological well-being. The panel research design gives us substantial leverage in inferring causation, leading us to believe that in thi s case, correlation does indeed imply causation. Initial Internet use and initial social involvement and psychological well-being were included in all of the models assessing the effects of Internet use on subsequent social and psychological outcomes. The refore, our analysis is equivalent to an analysis of change scores, controlling for regression towards the mean, unreliability, contemporaneous covariation between the outcome and the predictor variables, and other statistical artifacts (Cohen & Cohen , 1983). Because initial social involvement and psychological well-being generally were not associated with subsequent use of the Internet, after controlling for demographic characteristics, these findings imply that the direction of causation is more lik ely to be that use of the Internet led to declines in social involvement and psychological well-being, rather than the reverse. The only exception to this generalization was a marginal finding that people with larger local social circles were lighter user s of the Internet.

The major threat to the causal claim would arise if some unmeasured factor varying over time within individuals simultaneously caused increases in their use of the Internet and declines in their normal levels of social involvement and psychological wel l-being. One such factor might be changes in adolescence, which could cause teenagers to withdraw from social contact (at least from members of their families) and to use the Internet as an escape. Our data are mixed regarding this particular interpretati on. Tests of patterns of interaction of Internet use with age showed that increases in Internet use were associated with larger increases in loneliness (ß = -. 16, p <.02) and larger declines in social support (ß = -. 1 3, p <. 05) for teenagers than for adults. On the other hand, increases in Internet use were associated with smaller increases in daily stress for teenagers than adults (ß = -. 16, p <. 02). There were no statistical inter actions between Internet use and age for family communication, depression, or size of social circle.

Although the evidence is strong for the claim that Internet use caused declines in social participation and psychological well-being within this sample, we do not know how generalizable the findings are. The sample examined here was selected to be dive rse, but it is small and not statistically representative of any particular geographic region or population. Its demographic are skewed, over representing people in their teens and in their mid-30s to 50s and under representing people in their twenties an d in their retirement years. These latter groups are among the heaviest Internet users. Also, the sample examined people in their first one or two years on-line, starting in 1995 or 1996; whether results would have been the same at different points in the ir experience or at different points in the history of the Internet is unclear. Finally, the sample consisted of families with at least one member engaged in a pre-existing face-to-face group (students working on a high school newspaper or adults on the b oard of a community development organization). Whether the results would be the same for less socially engaged families is unclear.

Possible causal mechanisms.

To this point, we have attempted to establish the existence of a phenomenonóthat Internet use causes declines in social involvement and psychological well-being. We have not, however, identified the mechanisms through which this phenomenon occurs. There are at least two plausible and theoretically interesting mechanisms, but we have little evidence from our current research to established which, if either, is correct.

Displacing social activity. The time that people devote to using the Internet might substitute for time that they had previously spent engaged in social activities. According to this explanation, the Internet is similar to other passive, non-soc ial entertainment activities, such as watching TV, reading, or listening to music. Use of the Internet, like watching TV, may represent a privatization of entertainment, which could lead to social withdrawal and to declines in psychological well-being. Pu tnam (1997) made a similar claim about television viewing.

The problem with this explanation is that a major use of the Internet is explicitly social. People use the Internet to keep up with family and friends through electronic mail and on-line chats and to make new acquaintances through MUDs, chats, Usenet n ewsgroups, and Listservs. Our previous analyses showed that interpersonal communication was the dominant use of the Internet among the sample studied in this research (Kraut et al., 1998). They used the Internet more frequently for electronic mail than fo r the World Wide Web and used electronic mail first in sessions where they used both; their use of electronic mail was more stable over time than their use of the World Wide Web; and their greater use of email relative to the Web led them to use the Inter net more intensively at subsequent times and to increase their likelihood of continuing to use the Internet over a long period (Kraut et al, 1998). And we have seen previously that even social uses of the Internet were associated with negative outcomes. T hus, greater use of electronic mail was associated with increases in depression.

Displacing strong ties. The paradox we observe, then, is that the Internet is a social technology used for communication with individuals and groups but is associated with declines in social involvement and the psychological well-being that goes with social involvement. Perhaps, by using the Internet, people are substituting poorer quality social relationships for better relationships, that is, substituting weak ties for strong ones (e.g., Granovetter, 1973; Krackhardt, 1994). People can support strong ties electronically. Indeed, interviews with this sample revealed numerous instances in which participants kept up with physically distant parents or siblings, corresponded with children when they went off to college, rediscovered roommates from t he past, consoled distant friends who had suffered tragedy, or exchanged messages with high school classmates after school.

However, many of the on-line relationships in our sample, and especially the new ones, represent weak rather than strong ties. Examples include a woman who exchanged mittens with a stranger she met on a knitting listserv, a man who exchanged jokes and Scottish trivia with a colleague he met through an on-line tourist Web site, and an adolescent who exchanged (fictional) stories about his underwater exploits to other members of a scuba diving chat service. A few participants met new people on-line and h ad friendships with them. For instance, one teenager met his prom date on-line, and another woman met a couple in Canada whom she subsequently visited during her summer vacation. However, interviews with participants in this trial suggest that while makin g new friends on-line happened and was welcomed when it occurred, it did not counteract overall declines in real-world communication with family and friends. Our conclusions resonate with Katz and Aspdenís (1997) national survey data showing that only 22% of the respondents who had been using the Internet for two or more years had ever made a new friend on the Internet. While neither we nor Katz and Aspden provide comparison data, we wonder whether, in the real world, only a fifth of the population make a friend over a two year period.

On-line friendships are likely to be more limited than friendships supported by physical proximity. On-line friends are less likely than friends developed at school, work, church, or in the neighborhood to be available for help with tangible favors, su ch as offering small loans, rides, or baby-sitting. Because on-line friends are not embedded in the same day-to-day environment, they will be less likely to understand the context for conversation, making discussion more difficult (Clark, 1996) and render ing support less applicable. Even strong ties maintained at a distance through electronic communication are likely to be different in kind and perhaps diminished in strength compared to strong ties supported by physical proximity (Wellman & Wortley, 1 990). Both frequency of contact and the nature of the medium may contribute to this difference. For example, one of our participants who said that she appreciated the email correspondence she had with her college-aged daughter also noted that when her dau ghter was homesick or depressed, she reverted to telephone calls to provide support. Like that mother, many participants in our sample loved the convenience of the Internet. However, this convenience may induce people to substitute less involving electron ic interactions for more involving real-world ones.

Implications for policy and design

The negative effects of Internet use that we have documented here are not inevitable. Technologies are not immutable, especially not computing ones. Their effects will be shaped by how they are constructed by engineers, how they are deployed by ser vice providers, and how they are used by consumers. Designing technology and policy to avoid negative outcomes will depend on a more complete understanding of the mechanisms through which use of the Internet influences social involvement and psychological well-being. If we assume, for example, that the negative consequences of using the Internet occur at least partly because people spend more time and attention on weak ties and less time and attention on strong ties, then some design and policy solutions come easily to mind. Most public policy discussion of the Internet has focused on its potential benefits as an information resource and as a medium for commercial exchange. Research funding also heavily favors the development of better resources for effic ient information delivery and retrieval. Both policy and technology interventions to better support the Internetís uses for interpersonal communication could right this imbalance. For example, services for finding people are far less common, sophisticated or accurate than services for finding information and products. Online directories of email addresses are far less comprehensive than online directories of telephone numbers. Search services on the Internet, like Yahoo, Alta Vista, InfoSeek, and Lycos gr ew from sophisticated industrial and government-funded research programs in information retrieval; they are well known and heavily used. The initiative on digital libraries, funded by the National Science Foundation and DARPA, has a goal of making picture s, graphs, and video images as easy to search and retrieve as text. Comparable search capabilities for finding people based on their attributes are far less well supported. (See the research on collaborative filtering, e.g., Resnick & Varian, 1997, fo r an interesting exception.)

The interpersonal communication applications currently prevalent on the Internet are either neutral towards strong ties or tend to undercut rather than promote them. Because most Web sites, Usenet news groups, and listservs are topically organized, str angers are encouraged to read each othersí messages and exchange communication based on their common interests in soap operas, civil rights, stamp collecting, or other narrow topics. This communication is dominated by the designated topic and people are f requently discouraged by social pressure from straying from the topic. Although some of these groups (e.g., in the alt. Newsgroup hierarchy) are formed explicitly to provide support, and a few even encourage real-world friendships and tangible help, these are relatively few in comparison to the thousands of groups focused on professional advice, hobbies, and entertainment. Information and communication services that are geographically based and designed to support people who already know and care about ea ch other are even rarer. Some successful experiments at community-based on-line communication do exist (e.g., Carroll & Rosson, 1996) along with some successful commercial services that support pre-existing social relations (e.g., "buddy lists" in Ame rica On-Line's Instant Messenger product).

More intense development and deployment of services that support pre-existing communities and strong relationships should be encouraged. Government efforts to wire the nationís schools, for example, should consider on-line homework sessions for student s rather than just on-line reference works. The volunteers in churches, synagogues, and community groups building informational Web sites might discover that internal listservs and real-time communication services are more valuable.

 

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