Pers Ubiquit Comput (2005) 9: 404–412 DOI 10.1007/s00779-005-0032-9

O R I GI N A L A R T IC L E

Martin Colbert

Age differences rendezvousing: reminders for side-stepping

Received: 24 December 2004 / Accepted: 10 March 2005 / Published online: 23 August 2005 Ó Springer-Verlag London Limited 2005

Abstract This paper reports a diary study of the use of mobile telephones for rendezvousing by young adults (aged 18–30) and mature adults (aged 31–45) in the UK. A number of age differences were found. Specifically, 31–45s more frequently: (1) attributed problems rendezvousing to the overrunning of previous activities, and to the spontaneous performance of additional tasks (‘side-stepping’); (2) reported that ‘problem’ rendezvous resulted in unnecessary sacrifices; and (3) changed plans for the rendezvous. These differences arose, because additional family commitments encouraged 31–45s to pack their daily programme of activities more tightly than 18–30s. Mobile phones might better target 31–45s, if they, for example, enhanced To Do Lists with contextsensitive reminders, in the first instance, reminders triggered by location (GSM network cellID) and logging off from PCs. Keywords Mobile telephone Æ Communication Æ Personal coordination Æ Age differences Æ Personal calendars Æ Reminders Æ Location-based services

1 Introduction 1.1 Tailoring mobile phones and services The use of mobile phones by the general public is discretionary and has many degrees of freedom. The public can choose whether or not to use a mobile phone, and, if so, then which service they use, and how they use it. For example, a person who arrives early at a rendezvous point and wonders where their friend is, may use their mobile phone to communicate with their friend, refer to travel information and maps, track their friend’s posi-

tion (given the necessary permissions), or do nothing and just wait—they have a ‘lifestyle choice’. The current situation amounts to competitive market for alternative devices and services, and this competition encourages the diversification of systems to meet the requirements of particular user groups—all other things being equal, users would prefer a package of phone and services tailored for ‘people like them’, rather than a generic package suitable for a large, heterogeneous population. Tailoring packages of devices and services for different segments of the general public, then, is a current concern for the mobile phone industry. An essential step in the tailoring of devices and services is to identify different user groups, and outline their distinctive characteristics. These characteristics reflect differences in the kinds of task that each group performs, the contexts in which they perform these tasks, and the qualities of use that they value. Having characterised distinct groups, it is then possible for design to target one group or another. The user characteristic studied in this paper is age. Age differences are frequently important in consumer product design. In relation to mobile phones, recent work has identified age differences in contact management [1]. This study suggested that 25–35-year olds are different to 16–18s and 50–60s in that they do more work integrating contact details obtained with a range of media (face-to-face, via the telephone, e-mail, and SMS/ IM) (2003). Teenagers were distinctive in that they possessed a greater number of contacts, and tended to use the mobile phone more to store contact details. Additional information about differences in mobile phone use will assist the tailoring of products to particular user groups.

1.2 Young and mature mobile phone users M. Colbert School of Computing and Information Systems, Kingston University, Kingston Upon Thames, UK

An influential demographic observation about the adoption of ‘first generation’ (GSM) mobile phones was their rapid adoption by teenagers [2]. Adoption

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was rapid in this age group, because pre-paid subscription and device subsidy eliminated economic barriers to adoption, and teenagers benefited from the phone as a means of building solidarity and sharing experience among friends. They also recognised its symbolic value. Insights from teen studies have been used to tailor mobile phones and services to this age group [3]. Recent market reports predict that, by 2006, teens will again provide around three quarters of the demand for multimedia messaging services (MMS) [4]. The demographic observation that motivates this paper is that use of mobile phones tends to fall away for age groups in their mid 20s. Over 30-year olds use mobile phones about 25% less than the mean for the general public as a whole, and a lot less than 18–30year olds (18–30s use the mobile phone about 40% more than the average) (Norway 2002, cited in Ref. [2]). It is comforting for industry to believe that cohort effects underlie this reduction of phone use among mature adults. That is, today’s mature adults use their mobile phones less than teenagers, because todays mature adults grew up with land-line telephones. Today’s 18–30s, in contrast, are growing up with mobile phones, and so tomorrow’s mature adults will carry forward this high rate of mobile phone use. Cohort effects are comforting for the mobile industry, because they imply that usage in the population as a whole will increase over time—the ‘spike’ in current line graphs showing phone use by age, will become a ‘broader-based lump’, and finally, a plateau, as the first mobile generation grows up. However, another explanation for reduced mobile phone use in mature adults concerns differences in life situation. Teens, one imagines, are learning to live independently—they are single, perhaps attending college, and living in temporary accommodation. Mature adults, in contrast, have an established home, and are busy balancing commitments to work and family. Adults use mobile phones less, because a mobile phone is less useful in their situation. Different life-situation explanations are less comforting for the mobile industry, because they imply that high rates of mobile phone use throughout life are not inevitable—the benefits that users perceive as teenagers will not necessarily be perceived as adults. Habits may evolve away from mobile phones, should mobile phones cease to benefit the user’s changing needs. It is likely that both cohort- and life-situation effects impact observed phone use, and the relative importance of these factors may be different for different services. To better comprehend the influence of these factors, this paper will seek to explain any age difference identified in terms of cohort- and life-situation effects. 1.3 Rendezvousing Rendezvousing, here, is the informal co-ordination of a face-to-face meeting between friends and family. The

purpose of a rendezvous is to come together to participate in a subsequent activity, such as to ‘watch a movie’, or to ‘have lunch’. It is important that mobile phones and services for the general public support rendezvousing. Almost everybody rendezvous’, and quite often. A recent UK study reported that the average rate of rendezvousing among university students was about six per week, with a minimum three per week and a maximum of ten per week [5]. The majority of mobile phone users also think the phone is useful for rendezvousing. A pan-european survey reported that 69% of respondents agreed with the statement, ‘‘The mobile phone helps one to coordinate family and social activities’’. (EURESCOM P903 2000, cited in Ref. [2]). Coordination was also found to be the most common topic for text messages sent by Norwegian users (Telenor 2002, cited in Ref. [2]). There has been considerable interest in the general impact of mobile telephony on the process of coordinating everyday life, in particular, how communication en route enables the iterative, fine-tuning of arrangements, the softening of schedules, and the ‘resolution of difficult social situations’ (being late, unexpected participation etc). Mobile communication (between personal devices) also supports preparations prior to departure, because mobile phones make other individuals more reachable, wherever they are. This paper aims to extend previous work by focusing on differences in rendezvousing when performed by different age groups. A specific finding from the EURESCOM study, was that young persons were more likely to have a positive attitude towards use of the phone for co-ordination than mature persons. To what extent is this difference in attitude a cohort effect, or due to differences in life situation?

2 Aims This paper compares rendezvousing as performed by young and mature adults—18–30-year-olds and 31–45year-olds. The two groups are compared in terms of task goals, levels of performance, reasons for problems, planning and phone use associated with the rendezvous. Perhaps, different age groups have rendezvousing problems for different reasons, or prepare for rendezvous differently. The reduction in general phone use among mature adults leads us to expect that 31–45-yearolds will use the mobile phone less frequently for rendezvousing than 18–30s. Cohort effects suggest that 18–30-year-olds will make fuller use of their phone to re-plan their activities, soften schedules and resolve awkward situations—today’s 30–45s will have adopted a ‘mobile lifestyle’ less fully. Differences in life situation lead us to expect that 31–45s will have different kinds of rendezvous, and perhaps get more stressed about meeting up ‘successfully’.

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3 Method The method used here is a field study method that combines diary and questionnaire techniques. Paperbased, retrospective reports are used, because mobile technology is not yet sufficiently advanced to support complete data capture of rare, private and geographically dispersed in the field. Also, it is mistaken to distort the subject of study (communication in context) with intrusive data gathering techniques. In the future, it may be possible to use mobile devices and wireless networks to directly observe and record the behaviour of mobile participants and their context of use [6], and to augment traditional diary techniques with new media [7, 8]. Meanwhile, this combination of diary and questionnaire is a useful substitute (even if it does push these data gathering techniques to their limits), because it generates qualitative data about the nature of rendezvousing, plus quantitative data about users, the tasks and performance.

3.1 Participants The participants in the study were 39 students from the School of Computing and Information Systems, Kingston University. The aim of selecting participants was to obtain a sample that was balanced in terms of sex, despite the fact that the vast majority of students in the School are males. Between January 2001 and April 2002, students who took a module in human-computer interaction completed a diary as a minor part of coursework exercises. Three classes were set this coursework—the final year undergraduate classes of 2001 and 2002, and the class for postgraduates on a conversion course in 2002. At the outset of the study, a large number of machine-readable response sheets were printed, and then used as part of the diaries. After setting the coursework to three classes, there were not enough machine readable-sheets to set the coursework to a fourth class. Twenty-two female students completed a diary and consented to its anonymous use here–four undergraduates in 2001, six undergraduates in 2002 and 12 postgraduates in 2002. The diaries of 22 male students were then selected from the appropriate course module year, to match the female participants as closely as possible in terms of age, ethnic background, marital status, number of children, and mobile phone ownership. Other findings in the data obtained from these participants have been reported elsewhere [9,10]. Of the 44 participants, five did not state their age, and so were excluded from this analysis. Of the 39 participants remaining, 30 were between 18 and 30-years-old (mean age = 22 years 9 months) and nine were between 31 and 45-years-old (mean age = 36 years). Although sufficient to establish statistical significance, only nine participants in the mature group is less than desired. This figure is higher than many studies that involve students, but the

consequence is that the study becomes a ‘blunter instrument’—it may fail to identify significant differences that actually exist, and which would have been identified, had more mature adults participated. Both the 18–30s and the 31–45s comprised approximately equal numbers of males and females, and participants who, almost without exception, had access to a fixed phone, possessed an e-mail account in addition to their university account, and were registered as full-time students (see Table 1). Also, all participants lived within commuting distance of Kingston Upon Thames, a suburb of London, UK. However, the age groups were not identical in the following respects: – The 31–45 group comprised a higher proportion of married individuals, a higher proportion of individuals with children, a higher proportion of postgraduate students, and a few individuals who only had access to a mobile phone, but did not own one; – The 18–30 group comprised a higher proportion of frequent mobile phone users, and a higher proportion of students from an Asian or Far-Eastern ethnic background. The study participants, then, have the expected background rates of phone use and life situations for their age, and the 18–30 and 31–45 the groups are well balanced in terms of other characteristics. It should also be pointed out that postgraduate study is more like ‘real work’ than undergraduate study. Postgraduate courses run approximately 10 am–4 pm Monday to Friday in a 1 week on, 1 week off cycle, and in dedicated teaching laboratories. Students are expected to attend all week. Undergraduates have fewer scheduled teaching hours, and teaching takes place at many venues around campus. By including a mixture of undergraduate and postgraduate students, the ‘workday routines’ of these

Table 1 Participants: characteristics of 18–30 and 31–45 age groups Characteristics

Age groups 18–30

Sex (ratio male:female) Mean age (years months) Ethnic Background (Ratio White: Asian:Afro-Carib:FarEast: Other) Married (%) Have children (%) On postgraduate course (%) Full-time study (%) Amount of additional paid work (h/week) Own mobile phone (%) Have access to fixed phone (%) Have additional e-Mail (%) Frequent user of mobile phone (% >10 calls/week) Frequent user of fixed phone (% >10 calls/week)

31–45

1:1 4:5 22 years 9 months 36 years 11:12:2:2:3 5:2:2:0:0 3% 3% 50% 97% 8h

44% 56% 66% 100% 5h

93% 83% 97% 60%

78% 100% 100% 30%

30%

38%

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of other group members, superimposed upon an annotated map. During the diary-keeping period, participants were encouraged to complete their diary as soon as possible after the reported events, for example, before departure, when they arrived at the rendezvous point, or when they got home. For ethical and legal reasons, participants were also told that they were free to choose a time and place that was safe and suitable for thinking about and writing their diary. At the end of the diarykeeping period, diary keepers completed a further form, which summarised their diary and its completeness. Questionnaire responses were processed automatically by an occular reading machine, whose output was checked manually before being read into statistical analysis software.

participants is more representative of the public at large than many other university-based studies. However, the sample of mobile phone users who participated in this study, is not entirely representative of the general public. Many phone users have daily routines and communication habits unlike those of postgraduate or undergraduate students, and a university campus is unlike other workplaces. For example, all students are requested to turn off mobile phones in lecture theatres, libraries and teaching laboratories, and it is common to see students ‘popping out’ of these areas to use their phone, or attempting to use their phone discretely (when they should not perhaps be using it at all). Communicating about rendezvous by business managers or plumbers might be different. Also, the between groups variable (age) is confounded with ethnic background, and study status. Ethnic background is unlikely to be important—previous analysis of this data suggests that ethnic background only has some specific effects on communication for rendezvousing, but these effects are unlikely to effect age differences [10]. However, enrolment on a postgraduate course may imply higher than average motivation and work-related ambition, so study status may effect the mature group’s attitude towards rendezvousing and communication. The specific limitations of this study need to be borne in mind when discussing the results.

This section presents results in terms of rendezvousing tasks, rendezvousing outcomes, usage of communication services and user experience of communication. Significant differences between age groups are listed in Table 2. Statistical significance was calculated using an independent-sample, two-tailed ‘t’-test, when comparing numerical data, and the chi2 test, when comparing frequency data.

3.2 Diaries

4.1 Rendezvousing tasks

The diaries analysed here cover a 1 week period in January for postgraduates and 1 week in February for undergraduates—the term-time routine. Participants made one diary entry for each rendezvous event they attended. Each entry comprised: (1) an open-ended, narrative description in the diary keeper’s own words of what happened, and why; and (2) the diary keeper’s responses to a questionnaire, which asked for specific details of each rendezvous event. This questionnaire comprised 37 questions about the event, outcomes, and usage and user experience of communication, which concerned the rendezvous both before departure and en-route.

Both 18–30s and 31–45s reported, on average, just over five rendezvous per week. The 18–30s group reported 5.6 rendezvous per week and 31–45s reported 5.1 per week.

3.3 Procedure To ensure that diary entries included a full account of relevant information, at the outset of the study, all students were given an overview of future position-aware, computing and communications for mobile devices, and were introduced to the aims of the study and the obligations of diary keeping. Participants examined fixedaccess websites that provide map, transport and venue information, such as http://www.multimap.com and londontransport.co.uk. A possible future service was also described, which enabled each member of a small group to display on their mobile telephone the positions

4 Results

Table 2 Age differences rendezvousing Measure

18–30s

31–45s

Significance

Frequency rendezvousing problems attributed to overrunning of previous activity Frequency rendezvousing problems attributed to spontaneous additional tasks Frequency lost opportunities take the form of personal sacrifices Frequency with which plan changes (before departure and en route) Mean number of communications via e-mail per rendezvous Mean number of communications via text messaging per rendezvous

21%

39%

0.050

5%

17%

0.002

7%

22%

0.008

No. changes 0 | 1 | 2 | >2 44% 35% 9% 11% 0.40

No. changes 0 | 1 | 2 | >2 37% 24% 28% 9% 0.91

0.008

0.006

1.23

0.70

0.022

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This rate of rendezvousing is very similar to the rate obtained by a pilot study. This paper, then, is based upon 168 rendezvous reported by 18–30s and 46 rendezvous reported by 31–45s. Both 18–30s and 31–45s were not significantly different in terms of the mean size of the rendezvous—the mean number of other rendezvousers involved, including the diary keeper, was 3.7 people for both groups. An initial inspection of the means suggested that 31–45s were more likely to meet members of their immediate family (partners or children) than 18–30s (50 versus 22%), less likely to meet close friends (50 versus 65%), and more likely to meet at places where they had met before (78 versus 61%). However, these means are not significantly different (sig. = 0.102, 0.109 and 0.100, respectively). 4.2 Rendezvousing outcomes Both age groups reported that they met as initially agreed about 50% of the time. Again, this rate of ‘task success’ is very similar to the rate reported in previous studies. An initial inspection of the results suggested that 31–45s were more likely to report stress (60 versus 49%) and lost opportunity1. (57 versus 44%) as a result of failing to meet as agreed. However, these means are not significantly different (sig. = 0.112 and 0.152, respectively). Generally speaking, the 18–30s and 31–45s were not significantly different in terms of the frequency with which problems rendezvousing were attributed to various possible causes, such as disruption of the mode of travel, poor planning, lack of geographic information, or lack of information about the other person, or travel etc. However, 31–45s were more likely to attribute problems rendezvousing to the overrunning of previous activities and to the spontaneous performance of additional tasks-‘‘side-stepping’’2. [11] (see Table 2). When stress or lost opportunity occurred, the levels of stress or lost opportunity reported by 18–30s and 31– 45s were not different (approximately 2.3 and 2.0, respectively). Also, when lost opportunity occurred, the frequency with which various forms of lost oppurtunity3 werereported generally did not differ between groups. However, 31–45s more frequently reported making individual sacrifices, that is, lost the opportunity to

1 Lost opportunity, here, refers to the loss of not doing what the participant would have done, had the rendezvouzers met as initially agreed 2 For example, taking the opportunity to call in at the shops on the way to the rendezvous point 3 Kinds of lost opportunity, here, include restructing the post-rendezvous activity, reduced participation in this activity by one or more rendezvousers, nonly–participation in the activity, or cancellation of the whole activity

performing another activity important to their own lives, not necessarily important to other rendezvousers. 4.3 Usage and user experience of communication Both 18–30s and 31–45s did not differ in terms of the mean number of communications about the rendezvous made prior to departure or en route to the rendezvous point (3.11 versus 3.36 communications per rendezvous). Also, 18–30s and 31–45s did not differ in terms of the number of communications made via the telephone or voicemail (1.62 versus 2.17 phone calls per rendezvous, and 0.58 versus 0.72 voicemails per rendezvous). However, 31–45s were more likely to change the plan for the rendezvous at some point (either prior to departure or en route). Compared to 18–30s, 31–45s were particularly likely to change plan twice. The 31–45s group were also more likely to use e-mail at some point during the rendezvous, and less likely to use text messaging (see Table 2). The groups were not different in terms of user experience of communication4. either prior to departure or en route.

5 Discussion 5.1 Age differences rendezvousing Overall, then, rendezvousing by 31–45s differs from rendezvousing by 18–30s, in the following ways: (a) 31–45s more frequently attribute problems to the overrunning of previous activities, and to taking the opportunity to perform additional, spontaneous tasks (‘side-stepping’); (b) 31–45s more frequently report that the lost opportunities arising from problematic rendezvous take the form of individual sacrifices; (c) 31–45s more frequently change the plan for the rendezvous; and (d) 31–45s communicated less frequently via text messaging than 18–30s, and more frequently via e-mail than 18–30s. Free text entries in the diaries suggested that differences (a), (b) and (c) arise, because 31–45s have commitments to spouse and children, and so pack [12] their programme of daily life with planned activities more tightly than 18–30s. Previous activities are seen to overrun, because a 31–45s day is packed so tightly in advance that there is little ‘slack in the system’, and so a delay in departure has a knock-on effect upon later rendezvous. The day of an 18–30, in contrast, is less tightly packed, and

4

User experience, here, refers to ratings for satisfaction, frustration, mental effort, disruption, convenience and social acceptability of communication

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so there is more opportunity to ‘soften the schedule’ without having knock-on effects. ‘Side-stepping’ is seen as a more frequent cause of problems by 31–45s, because side-stepping is a useful technique for ‘‘getting everything done’’—it increases the proportion of time spent being ‘‘productive’’ relative to time spent travelling (which is ‘‘unproductive’’). For 18–30s, when side-stepping is necessary, it is less likely to precipitate rendezvousing problems, because there is more ‘slack in the system’. The 31–45s group are more likely to perceive lost opportunities in the form of personal sacrifices, because 31–45s are more aware of the activities they could have packed in to the time they ‘wasted’ failing to meet as initially agreed. It is as if 31–45s have a lengthy ‘To Do List’ [13] continually at the back of their minds—tasks that they would like to perform, if only they could find the time to do them. In contrast, 18–30s tend not to perceive waiting around for someone else to turn up as a ‘personal sacrifice’. The plan for a rendezvous is more likely to change with 31–45s, because 31–45s need to keep adjusting their plans to optimise the packing of activities in time and space. For example, a change of plan might take the form, ‘‘My son has decided to go to Scouts this evening, so if we put our meeting back a little, I can drop him off on the way to you’’. The 18–30s group change plan less often, because they do not seem to pack their programme of daily activities so tightly in advance, so they can make a new arrangement without adjusting or checking existing arrangements. The reason 31–45s are more concerned with squeezing in other activities around a rendezvous in order to remove items from their ‘To Do List’, or to remain inline with their daily programme, seems to be commitments to spouse and children, in addition to their studies (see figures for marital status and number of children in Table 1). Diaries suggested that 31–45s communicated relatively more via e-mail and less via text messaging for two reasons. First, 31–45s were more predictably at their desks, notably in teaching laboratories (where their mobile phone should be turned off), and so cheaply and almost immediately reached by e-mail. Second, 31–45s had yet to adopt text messaging to the extent of 18–30s. They did not usually communicate that way, and there is no special reason to do so for rendezvousing (see figures for mobile phone ownership and usage in Table 1). 5.2 Age-related reduction in mobile phone use: effects of cohort and life situation Contrary to expectations based on cohort effects, use of the mobile phone for rendezvousing was not reduced in the mature age group—18–30s and 31–45s used a mobile phone to communicate a similar number of times. The disjunction between meeting as initially agreed, and the rendezvous being problematic (leading to stress and lost opportunity) was also similar. This suggests that 31–45s understand very well how to use greater availability, and communication en route, to renegotiate and fine tune

arrangements, and so can use mobile communication to ‘soften schedules’ and smooth potentially awkward situations5. just as well as 18–30s. Given the opportunity, and a life situation that requires it, 31–45s are evidently able to evolve their mobile habits away from previous land-line habits well enough. This study is consistent with other work, which suggests that the expectations and attitudes of various kinds of new mobile phone user evolve quite rapidly within the first 6 weeks of ownership, particularly in relation to coordination [14, p 4]. The reduction in phone use with age reported in the EURSECOM study, then, may concern mobile phone use for other purposes, say, for group formation, sharing experience, or ‘work’-related communication. The only clear effect of cohort in this study was the greater use of text messaging by 18–30s, and the greater use of e-mail by 31–45s. The 31–45s group have never taken to text messaging that greatly. However, even this difference has overtones of the life situation. Postgraduates (in teaching laboratories where mobiles should be turned off) were often more predictably reachable by e-mail, and the way the labs are laid out, e-mail can be used more discretely than text messaging. So it could be argued that, far from being stuck in land-line habits, 31– 45s had, in fact, evolved a use of e-mail that was better suited to their current situation than text messaging. Overall, then, and with respect to communication for rendezvousing, and this population, life situation seems more important than cohort as a predictor of mobile phone use. Although this may not be the conclusion that industry hoped for (high rates of phone use will not necessarily be carried forward as young adults mature), it reassures us that adults can evolve their habits quite rapidly to make use of mobile telephony, if they can see how it benefits their situation. Also, the greater importance of life-situation over cohort in this respect may also explain the less positive attitude among mature adults towards communication as a means of coordination reported in the EURESCOM study (see Sect. 3.1)—although mature adults appreciate how to use the technology, they also appreciate how it fails to satisfy the demands of their tightly packed schedules. 5.3 Further studies In this study, only nine participants were in the 31–45s group, compared to 30 in the 18–30 age group. Conse-

5 The apparent increase in occurrence of stress and lost opportunity in 31–45s (which, recall, was not statistically significant), is taken to suggest, if anything that 31–45s have more reason to regard failure to meet as agreed to be problematic, because their daily programme of activity is more tightly packed. If 31–45s were less capable of using phones to soften schedules and smooth potentially awkward situations, then both the occurrence and reported levels of stress and lost opportunity would have been significantly higher for 31– 45s, and they were not

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quently, it is possible that this study did not identify all the age differences in rendezvousing that actually exist. If future studies involved more 31–45-year-olds, then they may be able to show that stress and lost opportunity is higher for 31–45s (in this study, an apparent increase was not significant), and that 31–45s tend to rendezvous more frequently with immediate family (in this study, an apparent tendency was again, not significant). Further studies may also identify the effects (if any) of the two confounding factors present in this study—ethnic background and study status (implying motivation and attitudes to work-related achievement). Although diary entries did not suggest such effects, it is certainly possible that the distinctive concern of 31–45s to ‘squeeze in more activities’ may reflect commitments to career and personal development, as well as commitments to spouse and children. Further studies may also confirm, or disconfirm the assertions about the life-styles of 18–30s and 31–45s implicit in the explanation for age differences presented here. For example, are the programmes of daily activities of 31–45s really more tightly packed in advance than 18–30s? Is side-stepping actually more frequent among 31–45s? Interviews about participants’ personal calendars, and additional items in the questionnaire may help answer these questions. Given the failure to show a reduction in mobile phone use with age in this study, it would also be interesting to study how successive cohorts of young and mature adults use mobile telephones for other purposes, such as group formation, sharing experience and ‘work’related communication. 5.4 Design implications: tailoring mobile phones and services to 31–45s The design of a successful package of device and services will be based on many observational and interview-

based studies. This section discusses context-sensitive reminders as a way of supporting ‘side-stepping’—the characteristic need of 31–45s—with particular regard to rendezvousing and students. Reminders are discussed here, because reminding oneself of incidental, secondary tasks, is fundamental to side-stepping, because it prepares rendezvousers for squeezing in a secondary task around the primary task (the rendezvous), should the opportunity arise. Recalling a secondary task also motivates attempts to gain an opportunity to ‘‘side-step’’ by travelling and/or communicating differently. Reminders, and being reminded, was a common theme in the results of a survey of working parents in the UK and US that concerned problematic issues in their everyday life [15]. Reminders may also prove to be more useful than ‘Locator’ services, if not more so, because the vast majority of rendezvous (78%) [9] occurred at familiar places (participants were students, not tourists). Rendezvousers probably know all they need to about relevant resources, they are just unreliable at remembering they want to make a visit. Assuming that an effective reminder occurs when (and where) a user has the opportunity to act upon it, a ‘Position-aware reminder’ application is suggested in Fig. 1 [16]. With this application, a user first notes down a task to perform, for example, to buy some headache pills from a chemist’s shop (Fig. 1a). The user then indicates where and when they want the reminder to be triggered, by drawing a circle, which encloses the chemist’s, and intersects with their likely routes (Fig. 1b). Finally, when actually en route to a rendezvous (Fig. 1c), the user is reminded of their extra task. This application seems most likely to be useful, when the rendezvous, and the route to it, are regular, say, collecting the kids from school, going to the gym, commuting home, etc. Interestingly, users of ‘De-De’, a context-enhanced phone recently trialed in Finland, sometimes used a

Fig. 1 A location-enhanced to do list for mobile phones. a notes task to perform, b where to perform it, c reminded if near

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location-aware text messaging facility based upon cellID to deliver ‘prompts’ to friends [17]. However, participants did not send reminder messages to themselves to help them side-step. On the face of it, the De-De findings appear to be inconsistent with the results of this paper. However, the participants were teenagers (so their lifesituations were not sufficiently ‘complicated’ to warrant extensive use of reminders). Also, sending reminders to oneself with a messaging application may not have been sufficiently obvious to participants (compared with, say, a location-enhanced To Do List, or personal calendar). And people have different strategies for organising their lives, anyway—not all people with complicated lives use personal organisers. The background rate of personal calendar use by participants in the De-De study is not reported. Perhaps some older participants, who already use elctronic personal organisers, and with a contextenhanced calendar, would have used De-De differently. The context cues used to trigger a reminderare also important. The remainder application in Fig. 1 assumed locational cues. However, an informal survey of another 20 students at Kingston University, suggests that reminders near the resource, or en route to a rendezvous point, are not always the best possible points for reminders to side-step, because these reminders will often be too late. The time for the rendezvous is now so close that there may be no time to take a detour, and renegotiating the rendezvous is likely to inconvenience other rendezvousers too much. Reminders en route or at the resource may also be inconvenient to the person being reminded—he or she may be driving, or on a crowded bus etc. The best possible reminder, and particularly the widest acceptable reminder, was often triggered by departure for the rendezvous point, i.e., leaving campus, or leaving home. In the long term, detection or disappearance of BlueTooth devices in teaching laboratories or at home, at the exits of campus buildings, in cars or at bus stops etc., could trigger timely reminders. However, the required BlueTooth infrastructure does not currently exist—only a few students own BlueTooth enabled phones, and only a few BlueTooth devices are located on campus. And users may feel that a BlueTooth infrastructure, just for ‘more timely’ reminders, is unnecessary. Kim recently conducted an exploratory user study with ‘Gate Reminder’ [18]. Located at the front door of a family home, Gate Reminder detects RFID tags on participants and objects as they cross the threshold, and displays visual reminders on screen. Although the form of interaction was satisfactory to many participants, the additional infrastructure was felt to be too ‘heavy weight’ given the benefits. Perhaps, then, we should design for the infrastructure that 31–45s already have at university. Consequently, in the short term, reminders on departure may be triggered by logging off from desktop PCs— recall that many of the mature participants reliably worked at PCs in their dedicated lab during the day. A reminder could be created and delivered at the PC (see Fig. 2). Alternatively, with a synchronised mobile de-

Fig. 2 A personal calendar for PCs

vice, a reminder could be created on the PC but delivered on a mobile phone, or created on a mobile device and then delivered at the PC. Since 31–45s more frequently attributed problems rendezvousing to the overrunning of previous activities, reminders are likely to be delivered on several occasions, before the user actually has the opportunity to ‘sidestep’. And given the desire and need to side-step, having requested a reminder, 31–45s will sometimes have performed their secondary task already elsewhere, by the time the initial reminder is triggered. Future studies need to assess whether the benefits of successful reminding outweigh the annoyance of unactionable or outdated reminders.

6 Closing remarks This paper reported some similarities and differences in the way 18–30s and 31–45s use mobile phones to rendezvous. The 31–45s group used the phone to communicate about the rendezvous just as frequently as 18–30s. However, 31–45s more frequently: (1) attributed problems rendezvousing to the overrunning of previous activities, and to the spontaneous performance of additional tasks (‘side-stepping’); (2) reported that ‘problem’ rendezvous resulted in unnecessary sacrifices; and (3) changed plans for the rendezvous. These differences are explained by the life situation of the participants (greater family commitments among 31–45s), rather than their cohort. Mobile phones might better target 31–45s, if they, for example, enhanced To Do Lists with contextsensitive reminders, in the first instance, reminders triggered by location (GSM network cellID) and logging off from PCs. Acknowledgement Thanks are due to Dana McKay and others at APCHI2004 for their many comments and contributions.

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