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Keywords:

  • Mobile communication;
  • general trust;
  • mobile texting;
  • tele-cocooning;
  • social scope

Abstract

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

The present study examines the tele-cocooning hypothesis in the context of general trust using a nationally representative survey of Japanese youth. We find that although frequency of texting is positively correlated with general trust, this correlation is spuriously caused by how heavy mobile texters interpret the words “most people” in the general trust measurement. Heavy users assume that “most people” only refers to friends, family, and others going to the same school. When the effect of the “most people” assumption is controlled, the positive association between texting and general trust disappears. Further exploration of the data shows that heavy texting nevertheless has negative implications for social tolerance and social caution, both of which are theoretically proximate to general trust.

With the increasing functionality and widespread use of mobile phones, the need for studies on the social consequences of mobile phone use is now widely recognized. Using the tele-cocooning hypothesis, we examine the possible negative relationship between mobile texting (hereafter, texting) and general trust. The tele-cocooning hypothesis states that texting is associated with increasingly insular communication because it strengthens core ties at the expense of interactions with lesser-known weak ties. In this study, we focus on two manifestations of such insular communications: narrow social scope and low general trust. Although mobile phones can be used in a variety of ways, we examine texting in this study because it is how young people most frequently use mobile phones (Lenhart, 2012).

We investigate these issues using a sample of Japanese youth, who have been among the earliest and heaviest adopters of texting in the world. Networked individualism, which is accelerated by the widespread use of mobile phones, requires that people develop new strategies and skills for handling problems (Rainie & Wellman, 2012). General trust serves as an important element of these strategies and skills because those distrustful of others cannot effectively make use of social capital embedded in human relationships (Yamagishi, 2011). Despite the great popularity of mobile communication, Japan has the lowest levels of general trust among East Asian countries. For example, results of the 2007 Pew Global Attitudes survey showed that 79% of respondents living in China agreed that “most people in society are trustworthy,” while only 43 percent of respondents living in Japan agreed with the same statement (Pew Research Global Attitudes Project, 2008). Why is mobile phone use in Japan so high when general trust is so low? In this study, we address this question by demonstrating that mobile texting among Japanese youth brings about tele-cocooning which narrows their social scope and lowers the level of general trust.

Tele-Cocooning: Insularity of mobile communication

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

Although texting can potentially be used to maintain and build new relationships, research from a variety of sources indicates that texting during youth typically involves the intensive exchange of short messages among intimate and homogeneous peers (e.g. Campbell & Kwak, 2012a; Ishii, 2006; Ling, 2004, 2008; Wilken, 2011). Typical Japanese high school students exchange text messages with two to five close friends, and these exchanges tend to take place in more geographically limited areas than do e-mail exchanges using personal computers (Miyata, Wellman, Boase, & Ikeda, 2005). With a few notable exceptions (e.g. Boase & Kobayashi, 2008), the selectivity associated with mobile communication is believed to support and strengthen existing ties rather than build new ones (Ling, 2008). These observations clearly indicate that mobile texting is used to bond with core peer groups.

The distinctive bonding nature of mobile texting has prompted concern about a dark side of mobile communication. If texting facilitates contact with close friends and family exclusively, and if it reduces heterogeneous encounters, it can have a cocooning effect by focusing one's attention on existing close relationships at the expense of reaching out to new people (Campbell & Kwak, 2012a; Gergen, 2008; Habuchi, 2005; Ling, 2008). Put differently, if we assume that the resources people have to spend on personal communication are finite, the tele-cocooning hypothesis predicts that continual contact via texting strengthens existing strong ties at the expense of interactions with others who are less familiar.

Although concerns about tele-cocooning appear repeatedly in the mobile communication literature, empirical tests of tele-cocooning have been limited to its effects on social networks. Campbell and Kwak (2012a) demonstrated that mobile-based political discussion with a small number of strong ties who mutually affirm political views may be associated with political demobilization. Similarly, Campbell and Kwak (2012b) showed that levels of open dialogue between people in small and like-minded strong-tie networks decreased slightly when political discussion was mediated by mobile phone use. Note, however, that a series of studies by Campbell and Kwak (2012a, 2012b) indicate that mobile-mediated discussion in large, like-minded, strong-tie networks may foster both open and active citizenship. On the other hand, Ling (2008) demonstrated that mobile communication positively correlates with the social cohesion of strong ties, and he also pointed out the possibility that mobile phone use supports the cultivation of strong ties at the expense of important weak ties.

Texting and General Trust

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

If texting is associated with the insularity of communication among strong ties with like-minded others, how is texting related to trust, especially general trust?

General trust is a general belief in human benevolence. It suggests that trustworthiness is an aspect of human nature and that most people can be trusted despite some exceptions. High general trust is useful in situations with high opportunity costs and social uncertainty (Yamagishi & Yamagishi, 1994; Yamagishi, 2011). Yamagishi and Yamagishi (1994) demonstrated through large-scale surveys and a carefully designed series of experiments that general trust is higher in the U.S. than in Japan1. Limited social mobility and a longer duration of committed relationships in Japan make both the opportunity cost of staying in stable relationships and the incentive for engaging in opportunistic behaviors low. If Japanese people behave opportunistically in their exclusive networks of committed relationships, they are likely to be ostracized. Furthermore, once ostracized, it is difficult to join other networks because those are exclusive as well, which makes the social consequences of being ostracized quite severe. The consequence of this extreme dependency on existing relationships implies that individuals can be “assured” that their close ties of friends, family, and school or workmates, will not behave opportunistically. Because people embedded in a tight web of committed relationships do not have to judge the trustworthiness of others, their level of general trust is low. To put it in Yamagishi's (2011) words, “assurance destroys general trust.”

Conversely, when social mobility is high, as it is in the U.S., opportunity cost increases because staying inside a network of stable, committed relationships makes it difficult to take advantage of outside opportunities. Having the social intelligence to judge others' trustworthiness and to develop new, cooperative relationships is adaptive under such conditions. As a result, general trust is a form of social intelligence that allows individuals to cope with greater social mobility and uncertainty (Yamagishi, 2011).

The committed relationships Yamagishi (2011) describes roughly correspond to the concept of strong ties, because both ideas are characterized by stability and mutually beneficial cooperation. Accordingly, if texting has a tele-cocooning effect, it should facilitate the formation of committed relationships. Hence, it is predicted that heavy texters will have lower levels of general trust.

Measurement of General Trust

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

One possible threat to research on this topic is the measurement of general trust. In most cases, general trust is measured with a standard question: “Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?” Similarly, Yamagishi and Yamagishi (1994) used multiple items to measure general trust, such as, “Most people are trustworthy,” “Most people trust others,” and “Most people are basically good and kind.” It is noteworthy that each of these items uses the phrase “most people,” and as Grootaert and Bastelaer (2002) have pointed out, the meaning of “most people” can vary across respondents, which makes the interpretation of such measures ambiguous (Delhey, Newton, & Welzel, 2011; Sturgis & Smith, 2010). Because the measured level of trust will naturally be higher when known others (rather than anonymous strangers) are the assumed referents, general trust will be overestimated when this occurs. Therefore, to assess the association between texting and general trust, the scope of “most people” should be fixed across respondents. This is not an easy task, however, because it may be that how one interprets the phrase “most people” is itself correlated with mobile phone use.

Hypotheses

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

If texting leads to network insularity, as the tele-cocooning hypothesis maintains, then heavier texting should be associated with a narrower definition of “most people.” This process could take place in two ways. First, because intensive texting with close others inside cocoons takes time, it may limit or reduce interactions with more distant others. In this case, ties with people outside of cocoons are more likely to decay, leading to decreased network size among heavy texters. This could lead to an overreferencing of close others when heavy texters answer general trust questions that use the words “most people.” Second, texting may not shrink users' personal networks into small cocoons by decaying weaker ties, but it may cognitively limit users' social horizons. Intensive texting to those one has strong ties with may chronically increase their cognitive accessibility, keeping them at the foremost of one's mind. In this case, when heavy texters are asked about “most people,” they may tend to think of those they text frequently as exemplars because these ties are readily accessible in memory. Given these two possible scenarios, the first hypothesis is:

  • H1: Frequency of texting is negatively associated with the perceived scope of “most people.”

If H1 is supported, a positive but spurious association between texting and general trust would be detected. Even if texting and general trust have no meaningful connection, the reported general trust of heavy texters would be higher merely because they are more likely to imagine known others (rather than anonymous strangers) as the referents of “most people.” For this reason, our second hypothesis states:

  • H2: The frequency of texting is positively associated with levels of general trust when the perceived scope of “most people” is not controlled.

As previously noted, the relationship in H2 is spurious if H1 is supported. If the scope of “most people” is held constant, then the tele-cocooning hypothesis predicts that the association between texting and general trust will be negative because the insular communication in committed relationships that is strengthened by texting will decrease general trust. Thus, we hypothesize that:

  • H2a: The positive association between the frequency of texting and levels of general trust becomes negative when the perceived scope of “most people” is controlled.

These three hypotheses test the implications of the tele-cocooning hypothesis for general trust and directly address issue of validity in the general trust measure. As noted, however, the standard measurement of general trust is not soundly appropriate to test the tele-cocooning hypothesis. For this reason we utilize two other dependent variables that do not use the phrase “most people” to measure, but are nonetheless theoretically proximate to general trust. We use the Caution Scale (Yamagishi & Yamagishi, 1994) and the Social Tolerance Scale (Ikeda & Kobayashi, 2008; Kobayashi, 2010), both of which are relevant to general trust measurement while circumventing the “most people” wording.

People who generally trust others do not have to be overly cautious because they can effectively cooperate with heterogeneous others, and because they are socially intelligent enough to distinguish trustworthy from untrustworthy people (Yamagishi, 2011). As expected, Yamagishi and Yamagishi (1994) found a negative correlation between general trust and caution in dealing with others. Therefore, if texting is negatively associated with general trust, it will be positively associated with caution in dealing with others.

  • H3a: Texting is positively associated with caution in dealing with others.

On the other hand, because those with higher general trust can develop cooperative relationships with a diverse range of people, they do not have to exclude potential partners in social exchanges who have different values or attitudes. People from outside of one's committed relationships tend to have different views and opinions, and they are a source of non-redundant information and new opportunities (Granovetter, 1973). If those with high general trust are good at cooperating with heterogeneous others from outside their intimate circle, they must also be socially tolerant of others in order to reduce opportunity costs. Accordingly, if texting is negatively associated with general trust, it will also be negatively associated with social tolerance.

  • H3b: Texting is negatively associated with social tolerance.

Method

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

Survey

Targeting Japanese adolescents aged from 8 to 18 years, a nationally representative drop-and-collect survey was fielded in the summer of 2009.2 First, all cities in Japan were organized by region and population size into 62 strata. Next, 100 primary sampling units (PSU) were randomly selected in each stratum in proportion to its population size. Then, 17 target respondents were randomly sampled in each PSU using basic registries of residents. This is a standard method that is widely used in Japan to produce representative samples. Of the 1,700 target respondents, valid responses were received from 1,002 (59%) individuals. To include school-related variables in the analyses, about 2.5% of respondents who were not in school (i.e., who were 18 years old and had graduated from high school at the time of the survey) were excluded from these analyses. Using 2005 census information, the sample was weighted using poststratification weights calculated from distributions of sex, age, and the population of each stratum.

Measurement

General Trust

General trust was measured by summing the scores for three items from the General Trust Scale (Yamagishi & Yamagishi, 1994). The items “Most people are trustworthy,” “Most people trust others,” and “Most people are basically good and kind” were measured using 4-point scales (α = 0.85, Range: 3–12, Mean = 7.98, SD = 0.05). Immediately after responding to the general trust items, a follow-up question asked respondents to indicate what “most people” meant, using the prompt: “What kind of people did you imagine as ‘most people’ when answering the three items above [general trust items]? Please circle all that apply below.” The multiple-choice format for this question had eight possible responses: “All of humanity, not only Japanese people,” “All Japanese people,” “People living in the same prefecture,” “People living in the same city, ward, town, or village,” “People living in the neighborhood (within an approximately 10-minute walk from my home),” “People going to the same school or working at the same place of work,” “Friends or acquaintances,” and “Parents, brothers, sisters, or other relatives.”

Caution in Dealing With Others

Caution in dealing with others was measured by summing the scores for the following three items from the Caution Scale (Yamagishi & Yamagishi, 1994): “People are only interested in their own welfare,” “In this society, one has to be alert or someone will take advantage of you,” and “In this society, one must be constantly afraid of being cheated.” The items were measured using 4-point scales (α = 0.72, Range: 3–12, Mean = 8.15, SD = 0.06). A larger value indicates greater caution in dealing with others. The correlation with general trust was –0.17 (p < .01).

Social Tolerance

Social tolerance was measured using the following item from the Social Tolerance Scale (Ikeda & Kobayashi, 2008; Kobayashi, 2010): “What do you think when you and the following people have different views or opinions?” The wording was slightly modified to suit adolescent respondents, who answered this question for their “Father,” “Mother,” “Close friends of the same generation,” and “Acquaintances of the same generation” using a 4-point scale: 4 = No problem having different opinions; 3 = Not a big problem having different opinions; 2 = I would prefer that we have the same opinions; and 1 = It would be better if we had the same opinions. Social tolerance scores were figured by summing across responses for the four referents (α = 0.84, Range: 4–16, Mean = 11.91, SD = 0.10). The correlation with general trust was 0.00 (n.s.)3.

Frequency of Mobile Texting

The frequency of outgoing and incoming mobile texting on an average day was measured using the following 6-point scale (one for outgoing, one for incoming): 1 = less than one message; 2 = 1–5 messages; 3 = 6–10 messages; 4 = 11–25 messages; 5 = 26–50 messages; 6 = 51 messages or more. The incoming and outgoing scales were summed to create a single measurement of the frequency of mobile texting (α = 0.96, Range: 2–12, Mean = 6.02, SD = 0.12).

Control Variables

The effects of generalized reciprocity (Putnam, 2000), participation in voluntary associations (Brehm & Rahn, 1997), and the general trust of guardians (Sturgis et al., 2010) were controlled because they are major sources of the general trust of adolescents.4 The general trust of guardians was available because this survey collected data from adolescents and their guardians. Sex, age, the type of school (elementary school, junior high school, high school, or college), and whether the school was highly ranked were also included as control variables. School rank was included because a previous study in Japan indicated a negative correlation between school rank and general trust among high school students (Kobayashi & Ikeda, 2007).

Results

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

About 51% of the sample reported using mobile phones, with a great deal of age-related variability. Six percent of 8-year-olds, 17% of 11-year-olds, and 33% of 12-year-olds reported using mobile phones. The jump between ages 11 and 12 reflects the fact that many adolescents start to use mobile phones when they enter junior high school. Likewise, there is another jump between ages 14 (48%) and 15 (82%), which is when students enter high school. One hundred percent of the 18-year-olds in our sample reported using mobile phones.

About 97% of mobile phone users in this sample were texters. The frequency distribution for outgoing mobile texting indicated that 11% of the sample averaged less than one text message a day, 35% sent 1–5 messages, 21% sent 6–10 messages, 16% sent 11–25 messages, 12% sent 26–50 messages, and 5% sent 51 messages or more. The frequency distribution for incoming mobile texting indicated that 11% of the sample averaged less than one message a day, 34% sent 1–5 messages, 22% sent 6–10 messages, 15% sent 11–25 messages, 14% sent 26–50 messages, and 5% sent 51 messages or more.

  • H1: Frequency of texting is negatively associated with the perceived scope of “most people.”

The “full sample” bars in Figure 1 show how respondents interpreted the term “most people” in General Trust Scale items. About 20% of the respondents endorsed the two most general interpretations (“All of humanity” and “All Japanese people”) that are the theoretical targets of the General Trust Scale. However, more than 50% of the respondents endorsed “Friends or acquaintances,” and about 40% interpreted “most people” to mean “People going to the same school” or “family members.” This result at least partially reflects the fact that the sample is limited to adolescents. Nevertheless, this variability in the interpretation of “most people” corroborates the findings from previous studies that cast doubt on the theoretical targets of the General Trust Scale (e.g. Grootaert & Bastelaer, 2002).

image

Figure 1. How respondents interpreted the phrase “most people” (MA, %)

Download figure to PowerPoint

Next, to test H1, a cluster analysis was performed to categorize the respondents according to their interpretation of “most people.” Defining similarity as Pearson's phi coefficients, a hierarchical cluster analysis employing Ward's method generated two clear clusters, which are labeled “Narrow scope cluster” and “Broad scope cluster” in Figure 1.

The most prominent feature of the narrow scope cluster (n = 666) is the high percentage of respondents who endorsed “Friends or acquaintances,” “People going to the same school,” and “Parents, brothers and sisters, or relatives.” Those in the broad scope cluster (n = 336) interpreted the “most people” phrase to mean “All of humanity” or “All Japanese people.” This means that about two thirds of the respondents interpreted “most people” more narrowly than the intended interpretation used in the development of the General Trust Scale. Next, a logistic regression was performed using cluster (0 = Narrow scope cluster and 1 = Broad scope cluster) as the dichotomous dependent variable (Table 1).

Table 1. Logistic regression model predicting the interpretations of “most people”
Dependent variable: Scope of “most people”(0: Narrow scope cluster, 1: Broad scope cluster)
coef. (B)
  1. a

    P<0.01,

  2. b

    P<0.05,

  3. c

    P<0.1.

  4. Standard errors in parentheses.

  5. Reference category of school: Elementary school.

Sex−0.54a
 (0.19)
Age0.01
 (0.09)
Junior high school1.92b
 (0.80)
High school2.33b
 (0.95)
Some college2.32c
 (1.16)
Academic-track school−0.02
 (0.08)
General trust of the guardian−0.16b
 (0.06)
Participation in voluntary association−0.14a
 (0.05)
Generalized reciprocity0.03
 (0.03)
Frequency of mobile texting−0.09b
 (0.04)
Constant0.36
 (1.15)
N437
Pseudo R-squared0.08

The N for the analysis was reduced to 437 because we analyzed the subsample of respondents who used mobile phones. Despite the extensive controls, the frequency of mobile texting had a significant negative association with the scope of “most people.” That is, the more frequently adolescents texted, the more likely they were to belong to the narrow scope cluster, which supports H1.

  • H2: The frequency of texting is positively associated with levels of general trust when the perceived scope of “most people” is not controlled.
  • H2a: The positive association between the frequency of texting and levels of general trust becomes negative when the perceived scope of “most people” is controlled.

To test H2 and H2a, ordinary least squares (OLS) regressions were conducted using general trust as the dependent variable (Table 2). To test H2, the magnitude of unmediated association between mobile texting and general trust was estimated without controlling for the scope of “most people” (Model 1). To test H2a, the dichotomous clusters of assumed “most people” was included as an independent variable to see whether the coefficient of mobile texting would be negative (Model 2).

Table 2. Regression models predicting general trust, caution in dealing with others, and social tolerance
Dependent variable:General trustCaution in dealing with othersSocial tolerance
model 1model 2model 1model 2model 1model 2
coef. (B)
  1. a

    P<0.01,

  2. b

    P<0.05,

  3. c

    P<0.1.

  4. Standard errors in parentheses.

  5. Reference category of school: Elementary school.

Sex−0.21−0.43a−0.59a−0.60a0.030.13
 (0.18)(0.14)(0.17)(0.16)(0.26)(0.25)
Age−0.08−0.080.000.000.34b0.34b
 (0.07)(0.08)(0.08)(0.09)(0.13)(0.13)
Junior high school−0.390.140.250.27−0.07−0.32
 (0.39)(0.40)(0.42)(0.41)(0.82)(0.80)
High school−0.75−0.080.440.47−0.12−0.44
 (0.53)(0.56)(0.58)(0.58)(1.09)(1.06)
Some college−1.13c−0.380.300.32−0.24−0.56
 (0.65)(0.69)(0.71)(0.72)(1.33)(1.30)
Academic-track school−0.12c−0.12c0.030.020.160.16
 (0.06)(0.07)(0.08)(0.08)(0.11)(0.11)
General trust of the guardian0.31a0.25a−0.15a−0.16a0.060.09
 (0.06)(0.06)(0.05)(0.05)(0.09)(0.09)
Participation in voluntary association0.20a0.15a−0.02−0.020.050.08
 (0.06)(0.05)(0.06)(0.06)(0.06)(0.06)
Generalized reciprocity0.12b0.130.20a0.20a−0.07−0.08
 (0.05)(0.05)(0.06)(0.06)(0.07)(0.07)
Frequency of mobile texting0.07b0.040.08b0.08b−0.13b−0.11b
 (0.03)(0.02)(0.03)(0.03)(0.05)(0.05)
Scope of “most people” −1.93a −0.08 0.87a
  (0.15) (0.21) (0.27)
Constant4.86a6.13a7.70a7.76a7.39a6.74a
 (1.18)(1.15)(1.10)(1.15)(1.78)(1.80)
N430430431431431431
R-squared0.140.300.080.080.070.09

In model 1, the frequency of mobile texting showed a positive association with general trust, which supports H2. That is, when general trust is measured with the phrase “most people,” the more frequently adolescents exchange texts, the greater their general trust appears to be. In model 2, in which the scope of “most people” was added as an independent variable, the effect of mobile texting disappeared, but it did not become negative, which does not support H2a. The effect of the scope of “most people” is large – the R-squared increased from 0.14 in model 1 to 0.30 in model 2, which means a large part of the variance in general trust is explained by how respondents interpret the term “most people” on the General Trust Scale. Put differently, those who have narrower scope of “most people” ostensibly tend to trust others. Combined with H1, these results indicate that heavier texting is associated with a narrower social scope of adolescents, which in turn spuriously inflates the level of general trust when it is measured with the phrase “most people.”

To explore why the coefficient of mobile texting did not become negative in Model 2, we controlled for the scope of “most people” in a more stringent way, by replacing the dichotomous cluster of assumed “most people” with seven dummy variables that correspond to the eight types of people that respondents used to indicate their understanding of “most people.” However, this approach did not change the results or provide additional insight (table not shown). This insignificance of mobile texting in model 2 can be explained in at least two ways. First, the scope of “most people” might have been inadequately measured. We used eight types of people to cover the range of possible definitions of “most people,” but respondents' interpretations of “most people” may have been more diverse than we anticipated. However, testing this possibility directly is difficult with the limited dataset at hand.

Second, the insignificance of mobile texting might be true, which implies that the tele-cocooning hypothesis is overstated and mobile texting has no negative associations with general trust. In other words, heavy texters are no less trusting of others than light texters, but they are not more trusting either. Testing this possibility with the General Trust Scale is inappropriate because this scale is contaminated by how people interpret “most people,” which in turn correlates with mobile texting. We need to use other dependent variables that avoid the ambiguity of “most people,” but are nonetheless theoretically proximate to general trust.

  • H3a: Texting is positively associated with caution in dealing with others.
  • H3b: Texting is negatively associated with social tolerance.

To test the tele-cocooning hypothesis without using the “most people” wording, OLS regressions were estimated using caution in dealing with others and social tolerance as dependent variables (Table 2). For both dependent variables, the scope of “most people” was included in model 2, but not in model 1. The scope of “most people” was not expected to change the coefficients of mobile texting because the scales of these two dependent variables do not use the phrase “most people.”

Results indicated that frequency of mobile texting was positively associated with caution in dealing with others (model 1), and this association did not change when the scope of “most people” was controlled (model 2), which supports H3a. The more frequently adolescents exchange texts, the more cautious they are in dealing with others.

The frequency of mobile texting was negatively associated with social tolerance (model 1), and this effect persisted in model 2 despite use of the scope of “most people” as a control variable, which supports H3b. The more frequently adolescents texts, the less tolerant they are of heterogeneous others. The scope of “most people” in model 2 had a significant positive coefficient, indicating that those who have a broad conception of “most people” tend to be more tolerant. Although the scope of “most people” was significant, it only slightly decreased the magnitude of the coefficient of mobile texting (from –0.13 to –0.11), indicating that the association between texting and social tolerance is not contaminated by the scope of “most people.”

Discussion

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies

The present study examined the tele-cocooning hypothesis in the context of social scope and general trust. The results show that although the frequency of mobile texting is positively associated with general trust (H2), the association is spurious, as it is generated by the tendency of heavy texters to have narrower scope of “most people” (as used in the measurement of general trust) (H1). When the misleading variation of the “most people” assumption is controlled, the positive association between texting and general trust disappears, but does not become negative (H2a). On the other hand, mobile texting is positively associated with caution in dealing with others and negatively with social tolerance (H3a, H3b). Although the tele-cocooning hypothesis was not clearly supported with respect to general trust, it was supported insofar as these results indicate that texting among adolescents is associated with cautiousness and social intolerance in dealing with others.

Despite its social significance, the tele-cocooning hypothesis has not received rigorous empirical scrutiny. Although ample evidence indicates that mobile phones are indispensable for many people because they allow close associates to remain in constant contact, clear-cut evidence addressing the possible negative consequences that might arise from frequent mobile usage is scant. Specifically, although some research partially supports the tele-cocooning hypothesis from a social network perspective, too little attention has been paid to the tele-cocooning hypothesis from cognitive and psychological perspectives. This study is the first step toward filling this gap in the literature. The unique contribution of this study is the identification of an overlooked association between texting and the validity of the measurement of general trust, i.e., the varying scope of “most people.”

Nevertheless, the findings reported here must be interpreted with caution because we did not include social network variables such as size, closure, and/or homogeneity of networks in the analyses. As such, it is still not clear whether the relationships between texting and the dependent variables are mediated by the insularity of social networks or whether they reflect cognitive and psychological processes that are not mediated by any social network variables. Moreover, considering that previous studies on the tele-cocooning hypothesis have rather consistently detected a moderating effect of network size (Campbell & Kwak, 2012a, 2012b), future studies should identify factors such as network size and motivation to use mobile phones that moderate the relationship between texting and trust-related variables.

Because the data in this study were collected before the widespread use of smartphones in Japan, we can safely assume that most of the mobile phone users in our study used “feature phones” that allow for a more limited number of functions. However, the rapid diffusion of smartphones is changing the basic conditions that underlie the tele-cocooning hypothesis. Smartphones have the potential to stimulate communication with heterogeneous others because they offer a greater range of applications than so called “feature phones.” These applications can be used to connect with social ties from diverse social groups (Hampton, Livio, & Goulet, 2010) and interact with others through social media (Donath & boyd, 2004). If smartphones facilitate weaker and more heterogeneous ties, the tele-cocooning effect of mobile texting may be mitigated.

However, a recent survey in the U.S. indicates that texting still dominates teens' general communication choices despite the rapid diffusion of smartphones (Lenhart, 2012). This contrasts with the fact that teens' frequency of voice calling using mobile phones is declining (Lenhart, 2012). Although Facebook is becoming increasingly popular in Japan as well as the U.S., it is still competing with other domestic social media such as Mixi (a domestic social networking site which had 13 million users at the end of 2012). Because the users of Mixi tend to form more insular networks of strong ties with like-minded others compared with international social media (Takahashi, 2010), social media use in Japan does not necessarily lead to an increase in weaker and more heterogeneous ties. Furthermore, the texting-like apps for smartphones such as LINE (an instant messaging application for smartphones and PCs which had more than 30 million users at the end of 2012) are attracting increasing numbers of people, facilitating intensive one-to-one communication with close others. That is, although smartphones have increased the customizability of mobile phones to a great extent, they may only strengthen the bonds among core groups. If so, the evolution of smartphones would maintain or even exacerbate the tele-cocooning effect.

Finally, there are a number of important limitations to this study. First, and most significantly, this is a correlational study using cross-sectional data that does not allow us to make strong causal inferences. It is quite possible that limited social scope and low levels of general trust facilitate mobile texting because texting offers suitable social affordances for communication with strong ties. Panel-design data coupled with sophisticated analytic techniques would be necessary to adequately infer causal direction. Second, the inappropriate measurement of general trust using scales that involve the words “most people” is thought to be the primary reason that H2a was rejected. Although we found evidence that supports the tele-cocooning hypothesis in the tests of H3a and H3b, it is still necessary to test the effect of mobile texting on general trust using other measurements. One potentially effective way to test the robustness of the present findings is to replicate this study using the general trust item in General Social Survey, which also includes the words “most people.” Third, this study measured the frequency of mobile texting by self-report measures. Self-report measures of the frequency of mobile communication, however, are prone to measurement error (Kobayashi & Boase, 2012; Boase & Ling, 2013). Measurement error may weaken correlations between variables, but it can also unduly inflate correlations, which increases the risk of type 1 error in statistical testing (Kobayashi & Boase, 2012). Fortunately, the diffusion of smartphones in recent years makes it easier to collect mobile communication logs automatically, decreasing the need to rely on self-report measures. Finally, given that there is evidence to suggest that voice calls are used to contact weak bridging ties while texts are used to contact strong bonding ties (e.g., Campbell & Kwak, 2010) future studies might examine whether the findings of this study can be generalized to other types of mobile communication. Future studies should also use adult samples to shed light on possible generational differences in the tele-cocooning effect.

Notes
  1. 1

    Higher general trust in the U.S. might be at odds with commonly held views about collectivism in Japan. See Takano and Osaka (1999) and Takano and Sogon (2008) for details about the lack of clear evidence of greater collectivism in Japan.

  2. 2

    This work was supported by NTT DOCOMO Mobile Society Research Institute.

  3. 3

    The insignificant correlation between general trust and social tolerance might reflect less conceptual proximity between these terms than there is between general trust and caution, which showed a significant negative correlation. Whereas general trust and caution directly speak to the risk of being exploited in a social exchange, one can be socially tolerant without actually engaging in social exchanges with heterogeneous others. Nonetheless, general trust and social tolerance are theoretically proximate; as Putnam (2000) has argued, bridging social capital promotes both general trust and tolerance.

  4. 4

    Generalized reciprocity refers to the normative recognition that if someone helps other people, they will receive help from others (not just from the people that they helped). This reciprocity creates a positive feedback loop that enhances the level of cooperation in social dilemmas, which in turn leads to greater general trust. We used the generalized reciprocity scale of Kobayashi, Ikeda, and Miyata (2006), modifying it slightly for adolescents: “When someone helps me, I will help someone else,” “When others are kind to me, I will be kind to someone else,” “When I see people helping each other, I also feel that I want to help people in trouble.” Responses to these items were measured on a 4-point scale and then summed to create a single generalized reciprocity score (alpha = 0.87, Range: 3–12, Mean = 9.95, SD = 0.53). Voluntary participation, which has been demonstrated to be a major predictor of general trust (e.g. Brehm & Rahn, 1997), was assessed with four items: “Club activities at school or place of work,” “Group of friends in cram school,” “Hobby or play group outside of school,” and “Volunteer group.” Respondents indicated their participation in these groups on a 3-point scale (1 = Not a member; 2 = A member but do not participate actively; and 3 = Participate actively as a member), and the responses were summed to determine their voluntary participation scores (alpha = 0.47, Range: 4–12, Mean = 7.07, SD = 0.05). The guardians' general trust was measured in the same way for the adolescents (alpha = 0.83, Range: 3–12, Mean = 7.12, SD = 0.04).

References

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies
  • Boase, J., & Kobayashi, T. (2008). Kei-Tying teens: Using mobile phone e-mail to bond, bridge, and break with social ties—a study of Japanese adolescents. International Journal of Human-Computer Studies, 66, 930943.
  • Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18, 508519.
  • Brehm, J. and Rahn, W. (1997). Individual-level evidence for the causes and consequences of social capital. American Journal of Political Science, 3. 9991023.
  • Campbell, S. W., & Kwak, N. (2010). Mobile communication and social capital: An investigation of geographically differentiated usage patterns. New Media and Society, 12, 435451.
  • Campbell, S. W. & Kwak, N. (2011). Mobile communication, social networks, and policy knowledge during the 2008 US presidential election. In J. Katz (Ed.), Mobile communication: Directions for social policy (pp. 103116). New Brunswick, NJ: Transaction Publishers.
  • Campbell, S. W. & Kwak, N. (2012a). Political involvement in “mobilized” society: The interactive relationships among mobile communication, network characteristics, and political participation. Journal of Communication, 61, 10051024.
  • Campbell, S. W. & Kwak, N. (2012b). Mobile communication and strong network ties: Shrinking or expanding spheres of public discourse? New Media & Society, 14, 262280.
  • Delhey, J., Newton, K., & Welzel, C. (2011). How general is trust in “most people”? Solving the radius of trust problem. American Sociological Review, 76, 786807.
  • Donath, J. & boyd, D. (2004). Public displays of connection. BT Technology Journal, 22, 7182.
  • Gergen, K. J. (2008). Mobile communication and the transformation of the democratic process. In J. Katz (Ed.), Handbook of mobile communication studies (pp. 297310). Cambridge, MA: MIT Press.
  • Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78, 13601380.
  • Grootaert, C. & Bastelaer, T. V. (2002). Understanding and measuring social capital: A multidisciplinary tool for practitioners. Washington: The World Bank.
  • Habuchi, I. (2005). Accelerating reflexivity. In M. Ito, D. Okabe & M. Matsuda (Eds.), Personal, portable, pedestrian: Mobile phones in Japanese life (pp. 165182). Cambridge, MA: MIT Press.
  • Hampton, K., Livio, O., & Goulet, L.S. (2010). The social life of wireless urban spaces: Internet use, social networks, and the public realm. Journal of Communication, 60, 701722.
  • Ikeda, K. & Kobayashi, T. (2008). Making democracy work via the functioning of heterogeneous personal networks: An empirical analysis based on a Japanese election study. In R. M. Hsung, N. Lin, & R. Breiger (Eds.), Contexts of social capital: Social networks in markets, communities and families (pp. 7290). London: Routledge.
  • Ishii, K. (2006). Implications of mobility: The uses of personal communication media in everyday life. Journal of Communication, 56, 346365.
  • Kobayashi, T., Ikeda, K., & Miyata, K. (2006). Social capital online: Collective use of the Internet and reciprocity as lubricants of democracy. Information, Community & Society, 9, 582611.
  • Kobayashi, T. & Ikeda, K. (2007). Jakunen-so no syakaika katei ni okeru keitai me-ru riyou no kouka: pa- sonaru nettowa-ku no dousitsusei/ishitsusei to kan-yousei ni chu-moku shite [The effect of mobile phone e-mailing in socialization in adolescents: Focusing on the homogeneity and heterogeneity of personal networks and tolerance], Syakai shinrigaku kenkyuu [Japanese Journal of Social Psychology], 23, 82–94. (In Japanese.)
  • Kobayashi, T. (2010). Bridging social capital in online communities: Heterogeneity and social tolerance of online game players in Japan. Human Communication Research, 36, 546569.
  • Kobayashi, T. & Boase, J. (2012). No such effect? The implications of measurement error in self-report measures of mobile communication use. Communication Methods and Measures, 6, 126143.
  • Lenhart, A. (2012). Teens, smartphones & texting. Pew Research Center's Internet & American Life Project. Retrieved June 25, 2012 from http://pewinternet.org/Reports/2012/Teens-and-smartphones.aspx
  • Ling, R. (2004). The mobile connection: The cell phone's impact on society. San Francisco: Morgan Kaufman Publishers.
  • Ling, R. (2008). New tech, new ties: How mobile communication is reshaping social cohesion. Cambridge, MA: MIT Press.
  • Miyata, K., Wellman, B., Boase, J., & Ikeda, K. (2005). The mobile-izing Japanese: Connecting to the Internet by PC and webphone in Yamanashi. In M. Ito, D. Okabe, & M. Matsuda (Eds.), The personal, portable, pedestrian: Mobile phones in Japanese life (pp. 143164). Cambridge: MIT Press.
  • Pew Research Global Attitudes Project (2008). Where trust is high, crime and corruption are Low. Retrieved September 13, 2013 from http://www.pewglobal.org/2008/04/15/where-trust-is-high-crime-and-corruption-are-low/
  • Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & Schuster.
  • Rainie, L. & Wellman, B. (2012). Networked: The new social operating system. Cambridge, MA: MIT Press.
  • Sturgis, P. & Smith, P. (2010). Assessing the validity of generalized trust questions: What kind of trust are we measuring? International Journal of Public Opinion Research, 22, 7492.
  • Sturgis, P., Read, S., Hatemi, P. K., Zhu, G., Trull, T., Wright, M. J., & Martin, N. J. (2010). A genetic basis for social trust? Political Behavior, 32, 205230.
  • Takahashi, T. (2010). MySpace or Mixi? Japanese engagement with SNS (social networking sites) in the global age. New Media & Society, 12, 453475.
  • Takano, Y. & Osaka, E. (1999). An unsupported common view: Comparing Japan and the U.S. on individualism/collectivism. Asian Journal of Social Psychology, 2, 311341.
  • Takano, Y. & Sogon, S. (2008). Are Japanese more collectivistic than Americans? Examining conformity in in-groups and the reference-group effect. Journal of Cross-Cultural Psychology, 39, 237250.
  • Wilken, R. (2011). Bonds and bridges: Mobile phone use and social capital debates. In R. Ling & S. Campbell (Eds.), Mobile communication: Bringing us together or tearing us apart? (pp. 127149). New Brunswick, NJ: Transaction Publishers.
  • Yamagishi, T. & Yamagishi, M. (1994). Trust and commitment in the United States and Japan. Motivation and Emotion, 18, 129166.
  • Yamagishi, T. (2011). Trust: The evolutionary game of mind and society. Tokyo: Springer.

Biographies

  1. Top of page
  2. Abstract
  3. Tele-Cocooning: Insularity of mobile communication
  4. Texting and General Trust
  5. Measurement of General Trust
  6. Hypotheses
  7. Method
  8. Results
  9. Discussion
  10. References
  11. Biographies
  • Tetsuro Kobayashi (Ph.D., University of Tokyo) is an Associate Professor at National Institute of Informatics in Japan. His research focuses on political communication and mobile communication in East Asian countries.

    Address:National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo, 101-8430 Japan.

  • Jeffrey Boase (Ph.D., University of Toronto) is an Assistant Professor in the School of Professional Communication at Ryerson University in Toronto. His research focuses on communication technology and personal networks.

    Address: School of Professional Communication, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3.