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Running head: MOBILE PHONE USE IN AA NETWORKS

Mobile Phone Use in AA Networks: An Exploratory Study

by
Scott W. Campbell

Assistant Professor and Pohs Fellow of Telecommunications

Department of Communication Studies

University of Michigan

3020D Frieze Building
105 South State St.
Ann Arbor, MI 48109-1285

Phone: (734) 764-8106

Email: swcamp@umich.edu
and
Michael J. Kelley (D.Phil., The University of Sussex, 1982)

Associate Professor of Psychology

Hawaii Pacific University

1188 Fort Street Mall

Honolulu, HI 96813

Phone: (808) 543-8045

Email: mjkelley@hpu.edu

Please note: For copyright purposes, this is a previous version of the manuscript. An updated version is forthcoming in Journal of Applied Communication Research.

Running head: MOBILE PHONE USE IN AA NETWORKS
Abstract

The purpose of this study was to explore the role of mobile phone use for mutual support within social networks of Alcoholic Anonymous (AA). A sample of mobile phone owners and non-owners in AA were surveyed to assess their perceptions and uses of this technology. Mobile phone owners reported very positive perceptions of the technology as a resource for recovery and heavy use of the mobile phone for this purpose. Non-owners also reported positive perceptions of the mobile phone as a resource for recovery, and that expense was the primary reason for not using a mobile phone in their recovery efforts. Heuristic, theoretical, and practical implications of the study are included in the discussion.

Over the last decade, mobile phone use has exploded to well over one billion subscribers worldwide. In fact, those who do not own a mobile phone have become a minority in several countries (International Telecommunication Union, 2004). Not surprisingly, such widespread diffusion and use of this burgeoning technology has led to myriad social ramifications. Some of these consequences include how people manage private boundaries in public places (Campbell, 2005a; Fortunati, 2003; Ling, 1996; Palen, Salzman, & Youngs, 2001; Wei & Leung, 1999), balance their personal and professional lives (Caporael & Xie, 2003), present themselves symbolically (Campbell, 2005b; Lobet-Maris, 2003; Katz & Sugiyama, in press; Skog, 2002; Strocchi, 2003), and interact in social networks (Campbell & Russo, 2003; Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 1999, 2002; Plant, 2001; Taylor & Harper, 2001). The purpose of the present study was to gain preliminary insights into mobile phone use within social networks for a new area of mobile communication research – mutual-help groups for alcohol-dependent individuals. We limited our scope to AA groups as these, at present, are by far the most dominant form of organized mutual-help group.

The ensuing literature shows that mobile phone use strengthens ties in social networks and that interaction within social networks plays a vital role in the recovery process used by AA and related programs. Drawing from these two areas of research and the theoretical orientation of Apparatgeist, the aim of this study was to test the supposition that mobile phone use plays a substantial role in the recovery of AA members. A sample of individuals in AA were surveyed to investigate whether and how they use the mobile phone for recovery, its perceived usefulness as a resource for recovery, and its use for recovery in relation to other communication channels. Non-mobile phone users were also included in the study to explore their perceptions of the technology and reasons why they do not use it. Even though this study offers heuristic, theoretical, and practical value, it is just a first step into this line of research and should therefore be regarded as exploratory in nature.


Mobile Phone Use in Social Networks


One of the prominent themes in the mobile communication literature is that mobile phone use strengthens social networks ties. The ability to connect with others anytime, anywhere allows for a state of “perpetual contact” (Katz & Aakhus, 2002) with social contacts, evidenced by the fact that 70% of respondents in a Pan European study agreed that the mobile phone allows them to stay in steady contact with family and friends (Ling, 2004b). One way the mobile phone is used to maintain social ties is through coordination of social activities. Sixty-nine percent of the respondents in the study cited above reported the mobile phone to be helpful in the coordination of activities with family and peers (Ling, 2004b). Ling and Yttri (1999, 2002) referred to these instrumental uses of mobile phone use as “microcoordination.” This type of mobile phone use includes basic logistics (e.g., redirecting trips that have already started), softening of time (e.g., calling someone to let him/her know you are running late), and progressive refinement of an activity, such as filling in details of open-ended plans (Ling, 2004b). A study by Campbell and Russo (2003) reported examples of microcoordination of social activity through collective mobile phone use within social networks. In one case, a group of sisters used the three-way calling feature to shop for a Father’s Day gift together, despite the fact that each sister was in a separate city. In another example, a group of friends collectively used their mobile phones to establish a meeting location at a crowded jazz festival. These findings illustrate how mobile phone use increases the ability to coordinate activities and bring network members together in ways that were previously not possible.

In addition to instrumental uses of the mobile phone for microcoordination, individuals use the technology in expressive ways to demonstrate and reinforce social network membership. Ling and Yttri (1999, 2002) dubbed such expressive use of the mobile phone as “hypercoordination.” Expressive use of the mobile phone may take the form of sustained interactions or short messages meant as gestures of social solidarity. Sustained mobile interactions include idle chatting (i.e., “small talk”) as well as discussion of more important personal matters (Johnsen, 2003). In either case, the conversation is laden with “expressive-symbolical content” (p. 164) with the bonding properties of relational glue. Licoppe (2003) described these sustained mobile exchanges as the “conversational mode,” characterized by “conversations that are generally spread out in time, long, and sometimes even ritualized, in which taking one’s time to converse is a sign of the strength of each person’s commitment to the relationship” (Licoppe, 2003, p. 181).

Merely placing a brief call or sending a short text message can also be an act of hypercoordination, even if the message lacks substantial content (Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 2002). On the surface, these types of messages may appear to be meaningless. However, as Johnsen (2003) explained, “The communication has … a very important function apart from the instrumental exchange of information. It becomes an information carrier-without having content or function except to sustain the idea of a social fellowship” (p. 163). These communication gestures, regarded as “the connected mode” by Licoppe (2003) and “digital gifts” by Johnsen (2003), are particularly common among adolescents and can be compared to the traditional teen practice of passing notes (Ling & Yttri, 2002). Although the digital “note” may lack content, there is an overriding meta-content. Ling and Yttri (2002) explained,

The receiver is in the thoughts of the sender and when they next meet they will be able to base a certain portion of their further interaction on the exchange of messages. The messages serve to tie the group together through the development of a common history or narrative (pp. 158-159).



Other distinctive forms of mobile communication practices are also used to demonstrate social network membership. One way this is achieved is through the numbers listed in one’s electronic phonebook stored in the handset. Green (2003) explained that having the “right” names stored in one’s handset helps “to demonstrate one’s participation in a peer community” (p. 207). Boundaries between network insiders and outsiders are also established through distinctive uses of voice calling and text messaging. For example, some Norwegian teens exclusively use voice calling with family members because it allows them to avoid calls from their parents by sending those calls directly to voice mail (Ling & Yttri, 2002). Furthermore, use of text messaging exclusively with peers allows teens to utilize characters and language unique to their social networks, hence performing network membership and sharpening the boundary separating insiders from outsiders (Ling & Yttri, 2002; Taylor & Harper, 2001). Collectively, these studies show that both instrumental and expressive uses of the mobile phone help establish, maintain, and strengthen relational ties within social networks.

Social Networks in Mutual-Help Groups for Alcohol Abuse

AA is the dominant recovery option in the United States for mutual-help approaches to alcohol dependence, and frequently used as aftercare to other professional treatments (Room & Greenfield, 1993). AA and related twelve-step professional treatment approaches to substance abuse have been shown to compare favorably to cognitive-behavior therapies on a broad range of outcome measures, in fact superior when total abstinence is used as the outcome measure (Ouimette, Finney, & Moos, 1997). The primary manifest ingredients to the success of AA and related programs are personal/spiritual development and the use of social support in the recovery process. Although the spiritual and social components are practiced hand-in-hand, the role of mobile phone use in spirituality per se lies beyond the scope of this paper; and therefore emphasis is placed on the role of communication within social networks.

The importance of social networks in AA can be seen in a number of ways, one being the nature of social contacts a recovering individual is encouraged to have. Newcomers to the AA program are often advised to change their social network by no longer associating with individuals who drink or use drugs. These individuals are also advised to regularly attend AA meetings, which encourages a change from pro-drinking to non-drinking social networks (McCrady, 2004). In addition to this practice, individuals in the program are advised to select and communicate regularly with a sponsor. Research indicates these social support practices in the AA program have a positive influence on recovery. For example, a longitudinal study of 654 AA participants looked at percentage of sobriety in the past 90 days. At a one-year follow-up interval, those reporting no social support only had 33% sobriety, and those with non-AA social support had 45% sobriety, whereas those with some AA-based social support had a sobriety rate of 72% (Kaskutas, Bond, & Humphreys, 2002). At a three-year follow-up on the same cohort, the number of AA-based contacts supporting reduced drinking was the only significant statistical mediator of AA’s effect on total abstinence (Jason, Kaskutas, & Weiser, 2003). Clearly interaction within social networks is a key component of the AA program and its success in the recovery process. With this in mind, the present study explored the extent to which mobile phone use plays a productive role in AA recovery networks.

Theoretical Grounding


The present study is framed by the theoretical orientation of Apparatgeist, conceived by Katz and Aakhus (2002) following an international workshop aimed at exploring the social implications of mobile communication. Apparatgeist, which literally means “machine spirit,” was advanced to make sense of consistencies and novelties in how people think about and use personal communication technologies (PCTs) such as the mobile phone. The aim of Apparatgeist is to help understand “how these technologies are recreated in the interests of the users, and with what intended and unintended consequences” (Katz & Aakhus, 2002, p. 303). Much of this theoretical orientation comes out of the patterns that Katz and Aakhus (2002) observed in research of mobile phone use in Finland, Israel, Italy, Korea, the United States, France, the Netherlands, and Bulgaria. Some of these patterns include new practices of intimacy and distancing, novel forms of coordination, changes in the ways people organize, challenges to existing communication routines, and frustrations with personal technologies.

According to Katz and Aakhus (2002) there is an underlying “logic” that contributes to the discernable trends associated with PCT use – the logic of perpetual contact. Perpetual contact stems from the human need to be able to connect with others, even to share one’s mind in a state of pure communication (Peters, 1999). Katz and Aakhus (2002) explained that perpetual contact is a “socio-logic” derived from collective sense-making, and it “underwrites how we judge, invent, and use communication technologies” (pg. 307).

The logic of perpetual contact is also shaped by a host of factors that are both social and technological in nature. Katz and Aakhus listed several examples of the social and technological attributes that factor into Apparatgeist, the logic of perpetual contact, and how people use the mobile phone and other PCTs. Among the social factors are personal needs, social roles, patterns of behavior, and network characteristics. Among the technological factors are functionality, cost, places of use, and ease of use (see Katz & Aakhus, 2002, pg. 311 for an expanded list of social and technological attributes). Consideration of these particular social and technological attributes in the context of the literature on mobile communication and AA social support practices lead to the overarching hypothesis of this study – that mobile phone use plays a substantial and positive role in the recovery process of AA members who own a mobile phone. Such a prediction is what Katz and Aakhus intended for Apparatgeist. They explained, “these premises can be used to generate empirical predictions about communication technology. They enable the individual, and, in turn collective entities, to make predictions about the performance of and uses for a technology” (p. 310). However, the authors also acknowledged that they provide only “the rudiments to establish a formal theory … these are only modest first steps in a long and complex journey” (p. 312). Thus, only the general prediction could be made that the mobile phone is useful to AA members in the recovery process, and research questions were used to investigate more specific aspects related to perceptions and uses of the mobile phone in AA networks. The first set of research questions were developed to explore the extent to which the mobile phone is regarded as a helpful tool in the recovery process, used for recovery-related purposes, and used for recovery in relation to other communication channels:

RQ1: To what extent do AA members who own a mobile phone regard it is a helpful tool in the recovery process?

RQ2: To what extent do AA members who own a mobile phone use the technology for recovery-related purposes?

RQ3: To what extent is the mobile phone used for recovery in relation to other communication channels?

In addition to how heavily the mobile phone is used for recovery-related purposes, the present study also sought to explore how it is used by AA members. The literature discussed above shows that two common uses of the mobile phone include instrumental and expressive interactions (Campbell & Russo, 2003; Ling, 2004b; Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 1999, 2002). The following research question helps explore the extent to which the mobile phone is used for these purposes in the recovery of AA members:

RQ4: To what extent do AA members who own a mobile phone use the medium for recovery-related purposes that are (a) expressive and (b) instrumental in nature?

This study also explored whether recovery-related mobile phone use is related to the age of participants. Age has been linked to perceptions and uses of mobile phones in a number of studies. Most notably, young people tend to use the mobile phone to demonstrate social network membership (Fortunati, 2002; Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 1999, 2002; Taylor & Harper, 2001) and regard the technology as a form of fashion (Alexander, 2000; Green, 2003; Ling, 2003; Lobet-Maris, 2003; Skog, 2002). In their explication of Apparatgeist, Katz and Aakhus discussed these trends as “a common, though likely implicit, orientation among teenage user groups” (p. 308). The following research question explores whether age is related to recovery-related mobile phone use:

RQ5: To what extent is recovery-related mobile phone use predicted by age?

Of course, not all members of AA own a mobile phone. Presumably, the cost of acquiring and using the technology prohibits some of these individuals from being mobile phone users, but other reasons should be explored as well. One of the aims of this study was to assess the attitudes of these individuals and to explore reasons why they have not adopted the technology. The following research questions were developed to examine these aspects of non-owners of mobile phones:

RQ6: To what extent do AA members who do not own a mobile phone view the medium as a potentially helpful tool in the recovery process?

RQ7a & b: To what extent do AA members who do not own a mobile phone report cost as the primary reason? What other reasons do they have for not owning a mobile phone?

Method


Participants

One hundred twenty-three AA members participated in this study (53% female, 47% male). The mean age of participants was 38. Forty-seven percent of the participants reported their highest level of education to be a high school diploma, 24% partially completed a college degree, 15% completed an undergraduate or associates degree, and 13% either completed or partially completed a graduate degree. The sample consisted of 102 mobile phone users and 21 non-users. Mobile phone users reported an average of 544 minutes of mobile phone use per month for calls and all other services, and had been using a mobile phone for 32 months on average.


Instrumentation


An original self-report survey containing 28 items was used to assess mobile phone users’ perceptions of the technology, its use for recovery-related purposes, the extent to which they use other communication channels for recovery-related purposes, and demographics. Twenty-two of the items were used for this study, and the others were included for use in another investigation. For the items assessing perceptions and uses of the mobile phone and use of other communication channels for recovery-related purposes, participants were asked to respond using a 5-point Likert scale, with response options ranging from “Strongly disagree” to “Strongly agree.” Other communication channels studied included face-to-face interaction, the landline telephone, e-mail, and other Internet functions. Participants were asked to provide written responses for the additional communication channels used for recovery, estimated monthly minutes of use, history of mobile phone ownership, percentage of total mobile phone use for recovery, and age. Participants were asked to circle the correct response options provided for sex and level of education.

To determine whether and how unitary items combined into meaningful groupings, a principal components factor analysis with a varimax rotation was conducted on the 10 items assessing perceptions and uses of the mobile phone as a resource for recovery. The criteria for loading on a factor were (1) an eigenvalue greater than 1.00, (2) a factor loading of at least .65, and (3) maximum loading on a secondary factor no more than .50. Two items were removed from the analysis for not meeting these criteria. The eight remaining items yielded two interpretable factors. Table 1 shows factor loadings, eigenvalues, Cronbach’s alphas, and summary statistics for each factor.

Five items loaded above .65 on the first factor. These items reflect the degree to which one uses the mobile phone to discuss personal matters pertaining to addiction recovery; therefore Factor 1 was labeled “expressive use.” The following survey items illustrate the expressive use factor: “I often use the mobile phone to talk about personal issues with my sponsor.” “I frequently use the mobile phone to share something with another person in AA.”

Three items loaded highly on Factor 2, each above .76. These items were labeled “instrumental use” because they represent mobile phone use to make arrangements with others for recovery-related meetings. For example, one of the items states, “I frequently use the mobile phone to make plans to meet with another member of AA.” Another item from the instrumental use factor is, “I do not use the mobile phone to schedule AA-related appointments.” Negatively-worded items, such as this one, were recoded for the analysis.


Table 1

Factor Eigenvalues, Percents of Variance, Scale Reliabilities, and Summary Statistics


Factors

Eigenvalue

% Variance

Alpha


M

SD

Range

Expressive use


3.51

35.14

.84

4.46

.49

2.80-5.00

Instrumental use

2.70

26.96

.73

4.17

.82

1.33-5.00

The 21 participants who did not own a mobile phone were asked to respond to a similar Likert-format questionnaire as the one provided to the mobile phone users. The items for the non-users were adapted to assess how they would use a mobile phone if they owned one. For example, while mobile phone owners were prompted with “I frequently use the mobile phone to make plans to meet with another member of AA,” non-owners were prompted with “If I owned a mobile phone, I would use it to make plans to meet with another member of AA.” Non-users of mobile phones were asked two additional items: one assessing the extent to which financial restrictions are the reason for not adopting a mobile phone, and the other asking them to list other reasons for not owning a mobile phone. Item groupings from the factor analysis of the mobile phone owners were used to assess the perceived value of expressive and instrumental uses of the mobile phone by non-owners. Reliability analyses showed that the items for expressive use and instrumental use grouped reliably with alphas of .80 and .73, respectively. Because this portion of the sample includes only 21 participants, factor analysis was not conducted, and these findings are qualified as particularly exploratory in nature.



Procedure

With permission from the university’s institutional review board, surveys were administered by three university student volunteers between October 2004 and January 2005. One hundred seventy-three AA members were asked to participate, and 123 volunteered, providing a response rate of 71%. Participants were recruited at various AA meeting locations in the Honolulu metropolitan area. In order not to interfere with the meetings, the researchers waited for the conclusion of the meetings to seek participation. Volunteers then completed the surveys on-site, which typically took 10 minutes.



Analysis

Mean scores and frequencies of unitary items were evaluated to determine the extent to which mobile phone owners in the study agreed that it is a helpful tool in the recovery process (RQ1) and the extent of their mobile phone use for recovery-related purposes (RQ2). To compare their use of the mobile phone for recovery in relation to other communication channels (RQ3), participants provided a rating for their recovery-related use of (a) face-to-face interactions, (b) the landline telephone, (c) the mobile phone, (d) e-mail, and (e) other Internet functions. A repeated-measures ANOVA was conducted to evaluate differences in these media use ratings. In addition, participants were asked to write in other communication channels used for recovery that were not listed on the survey. RQ4 explored the extent to which mobile phone owners used the device for recovery-related purposes that are (a) expressive and (b) instrumental in nature. Mean scores for the instrumental and expressive use factors were evaluated, and paired sample t-tests were performed to explore whether the difference between the means was significant. To assess whether age was a predictor of recovery-related mobile phone use (RQ5), bivariate linear regression analyses were run with age as the predictor variable and the criterion variables being (a) percent of total mobile phone use for recovery, (b) expressive use for recovery, and (c) instrumental use for recovery.

RQs 6 and 7 examined perceptions of participants who did not own a mobile phone and reasons why they had not adopted the technology. The mean score and response frequency for the item, “The mobile phone would be a helpful tool in the recovery process” were used to address RQ6. This research question was further answered by calculating mean scores for the expressive and instrumental use factors and performing paired sample t-tests to assess whether the difference was significant. RQ7 explored (a) the extent to which financial limitations prevented the non-mobile phone owners from adopting the technology and (b) other reasons why these individuals did not own a mobile phone. RQ7a was addressed by evaluating the mean score and response frequency for the survey item, “I do not own a mobile phone for financial reasons.” In order to address RQ7b, respondents were asked to write in other reasons for not owning a mobile phone, and those responses were examined to identify themes.

Results

Before reporting the results of each research question, the finding for the test of the overarching hypothesis will first be discussed here. Collectively, the findings reported below, particularly those for RQs1-4, support the overarching hypothesis that mobile phone use plays a substantial and positive role in the recovery process of AA members who own a mobile phone. That is, the results show that participants in the study regarded the mobile phone as a helpful resource for addiction recovery, and that they used it frequently for this purpose.



RQ1 examined the extent to which mobile phone owners in the study perceived the technology to be a helpful tool in the recovery process. Eighty-nine percent (n = 91/102) of the mobile phone users who participated in the study agreed or strongly agreed with the statement, “The mobile phone is a helpful tool in the recovery process.” In fact, 73% (n = 74) strongly agreed with this statement, while only 2% (n = 2) either disagreed or strongly disagreed with it. The mean score for this item was very high at 4.58/5.00 (SD = .81). RQ2 examined the extent to which mobile phone owners used the technology for recovery-related purposes. On average, these participants reported that 370 of the 548 minutes (67.46% , SD = 27.54) of their total mobile phone use was for recovery-related purposes. In summary, the results of RQs1 and 2 reveal that these AA members regarded the technology as a very useful AA resource and that they used it heavily for interactions pertaining to addiction recovery.

RQ3 compared mobile phone use for recovery-related purposes to the use of other communication channels. Participants rated face-to-face interaction the highest for recovery-related interaction (M = 4.69), followed by use of the mobile phone (M = 4.38), landline telephone (M = 4.36), e-mail (M = 2.74), and other Internet functions (M = 2.59) (see Table 2 for additional descriptive statistics). To determine whether media use ratings differed significantly from one another, a repeated measures ANOVA was conducted with the dependent variable being the rating for media use on a scale of one to five and the within-subjects factor being communication channel with five levels (mobile phone, landline telephone, face-to-face interaction, e-mail, and other Internet functions). Results revealed a significant effect for communication channel, Wilks’ Λ = .34, F (4, 94) = 44.88, p < .001, partial η2 = .66. Table 3 shows that most of the follow-up pairwise comparisons for media use ratings differed significantly, and several effect sizes were large with d > .90 (Green, Salkind, & Akey, 2000). 1 In order to protect against Type 1 error, a Bonferroni procedure was used, and comparisons were tested at the .05 divided by 10 or .005 level. Five respondents provided written responses for other communication channels used. These responses include letters (n = 3), pager (n = 1), and literature (n = 1). To summarize, participants reported heavy use of face-to-face interaction, the mobile phone, and the landline telephone for recovery-related communication, while computer-mediated communication and other channels were reportedly used considerably less for interactions pertaining to addiction recovery.


Table 2

Descriptive Statistics for Recovery Use Ratings for the Communication Channels


Communication Channels

M

SD


Range

Face-to-face interaction


4.69

.63

1-5

Mobile phone

4.38

.63

2-5

Landline telephone

4.36

1.03

1-5

E-mail

2.74

1.52

1-5

Other Internet (chat rooms, IM, bulletin boards, etc.)

2.59

1.52

1-5



Table 3

Pairwise Comparisons for Media Use Scores, Mobile Phone Users (n = 102)




Comparison

M1 (SD)

M2 (SD)

Mean Diff.

T

df

p

d

Face-to-face * mobile phone

4.69 (.63)

4.38 (.63)

.32

3.81

100

.000**

.38

Face-to-face * landline

4.69 (.63)

4.36 (1.03)

.34

3.56

100

.001**

.35

Face-to-face * e-mail

4.69 (.64)

2.74 (1.52)

1.94

11.60

97

.000**

1.17

Face-to-face * other Internet

4.69 (.64)

2.58 (1.52)

2.09

12.45

97

.000**

1.25

Mobile phone * landline

4.38 (.63)

4.36 (1.03)

.02

.18

100

.85

-

Mobile phone * e-mail

4.38 (.63)

2.74 (1.52)

1.63

11.18

97

.000**

1.12

Mobile phone * other Internet

4.38 (.63)

2.59 (1.52)

1.79

12.42

97

.000**

1.25

Landline * e-mail

4.34 (1.04)

2.74 (1.52)

1.59

8.97

97

.000**

.90

Landline * other Internet

4.34 (1.04)

2.59 (1.52)

1.74

9.14

97

.000**

.92

E-mail * other Internet

2.74 (1.52)

2.59 (1.52)

.15

1.73

97

.09

-

Note. M1 (SD) = Mean and standard deviation for the first medium in the comparison.

M2 (SD) = Mean and standard deviation for the second medium in the comparison.

* p < .005. ** p < .001.

In addition to how much participants used the mobile phone for recovery, this study explored how they used the technology in this process. Drawing from the literature on how people use the mobile phone, RQ4 explored the extent to which participants reportedly used the device for recovery-related purposes that are expressive and instrumental in nature. Participants reported high scores for both the expressive and instrumental use factors with mean scores of 4.46/5.00 (SD = .49) and 4.17/5.00 (SD = .82), respectively. A paired samples t-test revealed that the mean rating for expressive use was significantly higher than that for instrumental use, t(101) = 4.51, p < .001. The standardized effect index, d, was .45, a moderate value (Green, Salkind, & Akey, 2000).

RQ5 explored the role of age in recovery-related mobile phone use. Bivariate linear regression analyses were conducted to evaluate whether age was a predictor of (a) percent of total mobile phone use for recovery, (b) recovery-related instrumental use, and (c) recovery-related expressive use. Because three sets of regression analyses were performed, a Bonferroni procedure was used to protect against Type 1 error, and relationships were tested at the .05 divided by three or .017 level. Results revealed age to be a significant predictor of percent of total mobile phone use for recovery, r = .26, r square = .07, t(90) = 2.54, p < .017, but not a significant predictor of recovery-related expressive (p = .64) or instrumental use (p = .47) .

RQ6 investigated the perceived recovery value of the technology among participants who did not own a mobile phone, and RQ7 explored reasons why these individuals had not adopted one. Eighty-six percent (n = 18/21) of these respondents either agreed or strongly agreed with the statement, “The mobile phone would be a helpful tool in the recovery process.” Furthermore, the mean score for this item was high at 4.33/5.00 (SD = .86). Ratings for projected expressive and instrumental use of the mobile phone were also high with mean scores of 4.38/5.00 (SD = .73) and 4.08/5.00 (SD = .97), respectively. Results of a paired samples t-test showed that the difference between the scores for expressive and instrumental use approached significance, t(20) = 1.97, p = .06. In summary, the findings for RQ6 show that despite not owning a mobile phone, these participants generally believed the technology would be a useful resource for addiction recovery, and that they would use it frequently to coordinate plans with others in AA and to talk about recovery-related personal matters.

When asked why they did not own a mobile phone (RQ7), 81 percent of the participants agreed or strongly agreed that they did not own one for financial reasons. When asked to list other reasons for not owning a mobile phone, only three respondents provided a written response. One respondent explained he/she did not need a mobile phone because AA meetings provided sufficient recovery-related interaction; another preferred to use pay phones; and the third respondent explained, “I don’t like to be reached 24/7.” The remainder of the respondents provided expense as the sole reason for not owning a mobile phone (M = 4.14/5.00, SD = 1.39).

Discussion

The mobile communication literature illustrates how members of social networks frequently use the mobile phone to demonstrate and reinforce network ties (Campbell & Russo, 2003; Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 1999, 2002; Plant, 2001; Taylor & Harper, 2001). Other studies show that social ties make up an integral component of the addiction recovery process for AA members (Jason, Kaskutas, & Weiser, 2003; Kaskutas, Bond, & Humphreys, 2002; McCrady, 2004). Bringing together these distinct areas of research, the authors of this study hypothesized that mobile phone use plays a substantial role in the recovery process of AA members. The purpose of this study was to test this supposition, while exploring some of the finer points related to mobile phone use by AA members and the perceptions of individuals in AA who do not own a mobile phone. Findings show that the mobile phone was indeed regarded as a valuable resource for recovery-related communication, it was used heavily for this purpose, and that participants reportedly used it in both instrumental and (especially) expressive ways.

Some of the most interesting findings from this study can be found in the descriptive statistics. For example, 83% (n = 102/123) of the individuals sampled owned a mobile phone. This finding is indicative of the widespread adoption of the technology in recent years (International Telecommunication Union, 2004). While it provides additional evidence of the vast penetration of this emerging technology, such a finding also points to one of the challenges increasingly faced by mobile communication researchers – access to participants who do not own a mobile phone. An illustration of this can be seen in a recent study where Ling (2004a) reported a 100% adoption rate among a nationally representative sample of Norwegian adolescents. Findings from this study and others demonstrate that the mobile phone is quickly becoming an ordinary aspect of our daily lives, as did the television in the middle 20th century and the Internet in the late 20th century (Katz & Aakhus, 2002; Rice & Katz, 2003).

Another revealing statistic from this study is that participants reported 67% of their total mobile phone use to be for AA-related interactions. This information alone tells an interesting story about the role that the technology plays in the process of recovery from alcohol dependence among AA members. Individuals are now able to reach one another at times and places where access was previously not possible, and they are taking advantage of this in ways that are useful to both their own recovery and the recovery of others. It is also telling that mobile phone use for recovery ranks so highly when compared to the use of other communication channels. Only face-to-face interaction had a higher rating for recovery-related use than the mobile phone. This finding may be explained by the emphasis on regular attendance to AA meetings. It is clear from the data in our sample that mobile phone use has not replaced face-to-face interaction in recovery support networks, but rather it provides an important supplemental means for connecting with others in the program, at least in this one urban area. In more rural areas, this pattern may change.

As previously noted, age has been associated with certain uses of the mobile phone, particularly for demonstrating and reinforcing social network ties among young people (Fortunati, 2002; Johnsen, 2003; Licoppe, 2003; Ling & Yttri, 1999, 2002; Taylor & Harper, 2001). Considering this, it is no surprise that age was found to be a significant predictor of percentage of total mobile phone use for recovery. However, this finding merits a closer look. Although age was a significant predictor, it only accounted for 6.7% of the variance in the proportion of total mobile phone use that is for recovery-related communication. In other words, age was a weak predictor of recovery-related mobile phone use. In addition, it was not a significant predictor of either expressive or instrumental recovery-related mobile phone use. These findings may be interpreted as evidence that variables other than age provide a better explanation for how and why participants in this study use the mobile phone. One variable that deserves closer examination in future investigations is the nature of social networks in the AA program. In a study by Campbell and Russo (2003), social network membership significantly influenced perceptions and uses of mobile phones. Accordingly, it is quite possible that the social networks established in AA have distinctive properties that make the mobile phone a particularly valuable and heavily used resource, and that network characteristics provide a stronger explanation for perceptions and uses of the mobile phone among AA members than age.

Although the adoption rate of mobile telephony was remarkably high at 83%, some participants in the study did not have one. The findings show that despite not owning one, these individuals still had very positive assessments of the mobile phone’s value as a recovery-related resource, and that they would use it frequently to interact with other members in AA if they owned one. The overwhelming reason for not owning a mobile phone was the cost of the technology. Most of these participants (81%) agreed or strongly agreed that they did not own a mobile phone because of the expense, and only a few provided another reason for not owning one. These findings suggest that a segment of the AA population might benefit greatly from using a mobile phone for recovery-related communication, but that it is too cost-prohibitive for these individuals to explore this option.

Beyond providing insights into the perceptions and uses of the mobile phone among AA members, the present study offers theoretical value by demonstrating the predictive power of Apparatgeist. Katz and Aakhus (2002) acknowledged that they advanced only the fundamentals of a theory to explain and predict common orientations toward PCTs and their use. To date, only the explanatory capacity of Apparatgeist has been clearly demonstrated (Katz & Aakhus, 2002). This study takes a step forward by demonstrating its predictive value. By using Apparatgeist as a framework for bringing aspects of social context and technological capabilities into focus, this theoretical orientation guided the present authors to the accurate prediction that mobile phone use plays a substantial role in the recovery process of AA members. Additional theory building is warranted to refine and develop this perspective so that it can be used to make more specific predictions and testable hypotheses.

Although the findings of this study provide valuable insights into the ways and the extent to which AA members use the mobile phone for recovery, they must be qualified by some important limitations. Specifically, this investigation should be regarded as an exploratory study because of the size and nature of the sample. Due to limited resources, a small convenience sample was used, and future research is needed to obtain data from a randomly selected sample that is more representative of the population. The nature of this sample, especially the small number of non-mobile phone owners, hinders the generalizability of the results. Therefore, the findings of this study should be regarded as one glimpse into the mobile phone practices of AA members, and future research should be conducted to provide a more robust view of this social landscape. In addition to striving for more breadth, future investigations in this line of research should also endeavor for more depth. Qualitative approaches, such as interviews and focus groups, will help elicit a deeper, contextualized understanding of how individuals in AA use the mobile phone in their recovery efforts and may provide additional insights into the mobile communication practices that are associated with success in the program.

Practical Applications

Independent of whether the form of mutual-help group is AA or other social groups for assisting with issues of dependence, the mobile phone may be a helpful tool to use for relapse prevention. In cognitive-behavioral therapeutic interventions that focus on relapse prevention for drug use, major emphasis is typically placed upon how drug-dependent individuals are going to immediately cope with high-risk situations, particularly those that induce acute increases in negative affect (Witkiewitz & Marlatt, 2004). The present study provides some preliminary evidence that mobile phone use may be helpful to individuals who belong to recovery-related support networks. Whether mobile phone-mediated immediate access to members of mutual-help groups is an important, or an incidental, component for more successful relapse prevention seems worthy of further investigation.

Setting aside the issue of the potential clinical efficacy of mobile phone use in critical times of high risk for relapse, it is also possible to argue that an important practical application for individuals in recovery networks can be simply owning a mobile phone to generally seek out and provide social support to others and to make plans within support networks that foster reduced drug use. There may be may other practical advantages, such as the use of electronic phonebooks that store names and numbers in the handset. Green (2003) found that the names and numbers stored in one’s mobile phone help demonstrate membership and participation in his/her peer community. Considering AA members are encouraged to alter their social networks so that they no longer associate with substance abusers (McCrady, 2004), the electronic phonebook in a mobile may be a valuable resource for including certain individuals in one’s social network and excluding others from it. Furthermore, the speed-dial function associated with these electronic phonebooks may be an additional tool for easy access to social network ties in times of acute need for social support (e.g., during a moment of intense craving).

The findings of this study may also serve as grounds for seeking assistance for those individuals in recovery who cannot afford a mobile phone but would benefit from using one. The findings demonstrate that non-mobile phone owners in the study had very positive perceptions of the technology and believed they would use it frequently for recovery-related communication. However, they did not own a mobile phone because they could not afford one. These findings serve as grounds for additional research on AA members who do not own a mobile phone simply because they cannot afford it. Furthermore, this line of research may serve as justification for seeking a grant to help these individuals pay for a mobile phone and related services. With that said, it is important to acknowledge some challenges that need to carefully be examined in future investigations and grant-seeking. First, additional research is needed to better understand the potential negative consequences of mobile phone ownership and use in addiction recovery. For example, personal communication technologies, such as pagers and mobile phones, have notoriously been used by some individuals to buy and sell controlled substances. In addition, “drunk-dialing” has become a common mobile communication practice associated with binge drinking (Campbell & Russo, 2003; Lee, 2005). It is conceivable that owning a mobile phone could present a challenge to the sobriety of recovering individuals who have used the technology for such purposes in the past, and additional research is needed to explore these matters before attempts are made to provide assistance to those who cannot afford a mobile phone. Another challenge to be addressed is that AA as an organization does not accept any aid from external sources. Assistance to those who cannot afford a mobile phone would have to be communicated and administered purely on an individual bases. While these challenges are weighty, the findings of the present study indicate that they are worth pursuing so that recovering addicts who cannot afford to use a mobile phone might reap the same benefits from the technology as those who can.

Notes


  1. Green, Salkind, and Akey (2000) recommend using the d statistic as a measure for effect size of mean differences. Values for d can range from negative infinity to positive infinity, and absolute values of .2, .5, and .8 reflect small, medium, and large effect sizes, respectively.

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Witkiewitz, K., & Marlatt, G.A. (2004). That Was Zen, This Is Tao. American Psychologist, 59(4), 224-235.

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