Discovery of the ICT User Typology

Creating a Sampling Frame

Sampling in case studies is quite different from sampling in many other types of research. In case studies, participants (be they entire organizations or single individuals) are selected on theoretical reasoning and are not intended to form a representative sample. Instead, the selection of cases seeks to understand how these cases may differ based on theoretical differences (Yin, 2009).

There are many potential variables (suspected theoretical differences) I could have designed my case sampling frame to incorporate. Notable studies have examined how ICT use by older adults is impacted by living situation (community versus institutionally dwelling, rural versus urban) (Depatie & Bigbee, 2015; Parviainen & Pirhonen, 2017; Saunders, 2004), income (Bergström, 2017), socioeconomic class (Ihm & Hsieh, 2015; Iyer & Eastman, 2006; Parviainen & Pirhonen, 2017), education (González-Oñate et al., 2015; Vroman, Arthanat, & Lysack, 2015), experience with ICTs (Jacobson et al., 2017; Lee & Coughlin, 2015; Rosenthal, 2008), disability (Opalinski, 2001), and gender (Helsper, 2010; Padilla-Góngora et al., 2017). (Studies on the impact of race and ethnicity on older adult ICT use are unfortunately seriously lacking (Normie, 2003).) Incorporating all these variables into my case sampling frame would have been impossible, given the demands in time and resources such an intensive case study format requires.

Work was an important context I wanted to capture, so work status became the first theoretical difference in my sampling frame. Older adults who are retired often are the ones that volunteer for research, due to their more flexible schedules (Bouma, 2001; van Bronswijk et al., 2002; van Bronswijk et al., 2009). This has often prevented us from understanding the experiences of working older adults. In order to ensure I had working older adults in my study, I would have to seek them out.

Gender has long been conceptualized in the literature as being an important variable impacting older adult ICT use (Helsper, 2010), so gender was selected as a second theoretical difference for my sampling frame. Gerontechnology research has found that women tend to have greater difficulties in learning to use computers in the same settings as men (Hill et al., 2008; Ng, 2008; Shoemaker, 2003) and report lower usage rates (Helsper, 2010; Kim et al., 2017). Research in the domestication sphere (i.e., age diverse) has found that men and women often use technologies for drastically different reasons: men tend to use them for escape and to avoid socialization, women use these ICTs for interaction, socialization, and engagement with others (Lie, 1996; Livingstone, 1994), and women prefer personal ICTs over ones they view as impersonal (Singh, 2001). Having established gender as an important case sampling criterion, I realized from my readings on the Lucky Few birth cohort, that while many women from this cohort worked or were still working, there were also women who had chosen to stay at home after their children were born and remained housewives (Carlson, 2008). ⁵ I expanded my conceptualization of work to include those that had stayed at home.

I created a sampling frame (Table 4) which sought to recruit men and women who were still working part-time, still working full time, retired, and women who had stayed at home for the majority of their lives. ⁶ I defined work as “work for pay” and set full-time workforce participation to be more than 30 hours a week of paid work, and part-time participation as less than 30 hours of paid work per week. Retired older adults were those that no longer worked for pay, but once had. I sought to recruit at least one participant who met each combination of case sampling criteria. Such a framework was intended to allow for literal replications (Yin, 2009) (comparisons across cases I thought would be similar due to similar work status or gender) as well as theoretical replications (Yin, 2009) (comparisons between cases where I expected contrasting results because of different work statuses or between men and women). ⁷

This sampling frame represented some issues that needed to be navigated during the study. Older adult’s “self-descriptions” often did not match my own definitions when it came to work. Boris, who was self-employed in construction, tended to work about 50–60 hours a week during the summer, but often did not work during the two coldest winter months. Jackie was currently working part-time at multiple jobs while searching for additional employment. While Boris described himself as “semi-retired” (as in his youth he had often worked more than 80 hours a week in the summer), Jackie spoke about “working full-time” (despite the fact that her current work hours fell under 20 per week). Therefore, it became critical to discuss with the older adult during the recruitment phase as to what they meant by their self-description, asking them to provide the specific number of hours and months they worked.

I realized that many of the commonly used recruitment strategies when studying older adults (Birkland & Kaarst-Brown, 2010) would not suffice to fill this sampling frame. I could not go to a retirement community or a managed care setting and find older adults actively working full time. The strategy I eventually developed, based on snowball sampling (Goodman, 1961), sought to overcome the challenges of recruiting community-dwelling older adults.

Recruitment of Older Adults: Primary Participants

In the Gerontechnology literature, there has been a focus on recruiting older adult participants primarily from managed care residential settings or retirement communities (Birkland & Kaarst-Brown, 2010). A large population of older adults are available at these settings, and often residents are eager to be involved in projects with outside individuals for a change of pace from their typical days. While such samples are convenient for researchers, they are problematic, as only a small portion of older adults live in such settings. ⁸ These communities and institutions often restrict or, conversely, offer ICTs that the general older adult population may or may not have access to. For instance, Nancy’s assisted living center prohibited residents from using social networking sites by blocking them, but also provided a gaming console.

Those in such captive settings, such as retirement homes and graduated care, are easy for us as researchers to access, and by that measure, we often select from them liberally. There are some very concerning ethical issues in basing much of our gerontechnological research on captive populations (Birkland & Kaarst-Brown, 2010), who may feel unable to refuse participation (Reich, 1978).

In order to overcome these sampling issues, I decided to use a referent snowballing (Goodman, 1961) recruitment method, often advised to recruit older adults over “cold calling” potential participants (Johnson & Finn, 2017). In my home institution, I approached faculty, staff, and students (as well as my neighbors) asking if they knew an older adult who met the case selection criteria and would be willing to participate. Many times, if they referred me to individuals who themselves did not meet the selection criteria, these individuals had a contact who did.

This referent-based recruitment method proved useful in attracting participants who were able to meet the demanding nature of the study. With approximately 6–10 hours of the primary participant’s time spent in interviews (with an open-ended 2- to 3.5-hour segment of time needing to be scheduled for each interview), additional time spent in observations in the participant’s own home, and being asked to interview two to three potential friends, family members, or coworkers, this was a demanding study. ⁹ Compared to our stereotypes about older adults having large amounts of free time, many are busy with their leisure, community, family and (in many cases) their work lives (Bouma, 2001; Choi, Burr, Mutchler, & Caro, 2007; Eggebeen & Hogan, 1990; van Bronswijk et al., 2002).

Referents, therefore, served an important role in recruitment. Participants were not approached by a stranger, but rather a friend, family member, neighbor, or professional contact. Referents were able to describe not only the study but answer any questions the potential participant had about it at the outset, as well as vouch for me personally. Almost any person would be hesitant to allow a stranger into their home to view their technology for their own safety (such a research study would appear to be an almost perfect cover to allow criminals into your home). Additionally, referents were able to reassure potential participants that I was indeed interested in both use and non-use and that I was not trying to evangelize technology use or judge non-users. ¹⁰

Such a referent recruitment method proved extremely successful, meeting the case sampling framework. Participants were well-aware of the steep requirements of the study from both the referent and myself, and this resulted in every older adult who enrolled in the study completing all three interviews, for a total of 17 older adult primary participants (cases). (Secondary participants were not able to be recruited for all cases, as some older adults had very small social networks.) Only one person who was referred to me (who meet the selection criteria) declined to participate.

Near the middle of data collection, I realized that while I was likely to meet my sampling frame for the study, and had achieved an educationally, work status, and income diverse sample; racial diversity was lacking. My sample identified almost entirely as white, with one participant who identified as Hispanic/White. I had serious concerns about the overwhelming whiteness represented in many gerontechnological studies (Normie, 2003) and how this further silenced older adults of color. I wanted to include voices from this often ignored a segment of the older adult population.

Older individuals of color have extremely valid reasons to not participate in research. Research’s abusive and racist history is not just “historical”: many older adults remember these abuses when they happened (or were revealed) – in their own lifetimes. The university I was working from at the time also had a contentious relationship with the local communities of people of color. Located near one of the most impoverished sections of a racially segregated city, the university had a multi-decade history of starting community projects, promising long-term investment, obtaining research results, and quickly abandoning these projects with promises unfulfilled. As a white researcher from this institution, I would understandably be mistrusted from the start.

I decided that I needed a strategy to personally build trust with the older adults in the nearby communities. I reached out to six community organizations in my city, asking if I could join their community meetings for a period of time in order to eventually recruit participants. One community organization allowed me to do so, and I attended a series of meetings to become familiar with attendees and to build greater trust. ¹¹ After several attendances, I was approached by two African American women. I ended up recruiting both women (Gwen and June), which greatly added to the diversity of voices.

Originally, I had determined that I would not include participants from residential care settings in my study. My original reasoning for not recruiting directly from these settings was to avoid the unnecessary burden that had been placed on these individuals by their over-selection. I also wanted to remove possible ethical concerns around consent. One of my contacts referred me to her mother, Nancy, who lived in an assisted living facility. Upon considering her inclusion, I realized that for Nancy, her home was the assisted living center she lived in. For many older adults, their home is their assisted living center, nursing home, or retirement community. I was not selecting her because she lived in assisted living, but because she met the criteria of the study.

As I considered the issue even further, I realized that not allowing Nancy to participate in the study simply because she had made her home in an assisted living center would be unfair to her. If my goal was to hear from the older adults themselves – to have them voice their joys, struggles, and concerns over ICT use – then I had no reason to exclude an older adult’s voice because of where they had made their home. The next day I received a call from Nancy herself, asking to be included in the study and sharing a bit of her story. While I had a few participants who had contacted me (as opposed to me contacting them as a referral), she was the only participant who contacted me to argue their case to be included. Quite frankly, I admired her tenacity and knew I could learn something from her case.

The data that I collected from Nancy were extremely rich and added deeply to my understanding of the ICT User Typology. As a Socializer, Nancy found herself often prevented from using the ICTs she wanted to by disability or policy (see Chapter 4). Nancy’s case illustrated physical and policy concerns that I would not have captured without her inclusion.

While the primary participants for the study were selected based on the sampling criteria, secondary participants were identified and recruited based on the recommendation of the primary participant for each case.

Secondary Participants Recruitment and Sampling

For secondary participant recruitment, I asked the older adult at the center of each case (the primary participant) to identify individuals they used ICTs with (be it the phone, cell phone, computer, television, etc.). I asked them to identify one person who was of the same birth cohort as themselves (the Lucky Few generation) and one to two people who were either older (WWII/ Good Warrior Generation) or younger (Boomer, Generation X, or Millennial). ¹² These relationships could be of any type: romantic, family, friendship, coworker, etc. Therefore, of the two to three people I asked them to identify, one had to be of the same birth cohort, and two were from a different birth cohort. ¹³

In some cases, I ended up recruiting Lucky Few secondary participants to become primary participants in my study. This yielded very rich data, as I could understand from multiple perspectives how these individuals used ICTs in their relationships with others. This type of recruitment happened specifically for Jackie (who was recruited from Natalie’s network) and Fred (who was recruited from Alice’s network).

Each case involved several forms of data collection, including interviews, observations, and reviews of documentation that older adults used in their support of ICTs.

Recruiting Community-dwelling Working Older Adults

Recruiting community-dwelling older adults has sometimes been a challenge in the gerontechnological literature, due to older adults’ busy lives (Bouma, 2001). In particular, it has often been difficult to recruit older adults who are not participants of community center programs or programs designed specifically for seniors (Birkland & Kaarst-Brown, 2010). Many older adults do not participate in such programs, and attendance of such programs may be difficult for working older adults due to scheduling. ¹⁵

An extremely diverse sample of participants was recruited through the snowball referent methodology (Goodman, 1961). The sample included college professors, nurses, administrative assistants, electricians, contractors, retail workers, and retirees; those with extremely low incomes that depended on government assistance and those with high incomes who had retired early; those who worked as directors and VPs and those who had been front-line retail employees and administrative assistants; those that did not finish high school and even two participants with doctorates (one a PhD and one a professional doctorate). Participants lived in the inner city, urban areas, a host of suburban areas, rural towns, and in extremely rural areas. (The only aspect of diversity which fell short was racial, addressed previously in this chapter.) I cannot envision any other methodology allowing recruitment of such a diverse sample, given the unequal spread of potential recruitment sites across the geographical area.

With the exception of two of the participants whom I had met before, all the other 15 participants were total strangers to me at the outset of the study. Despite our unfamiliarity, these participants were willing to share some of their most sensitive stories with me, in part, because I had been recommended to them by someone they trusted (a friend, family member, or community contact). The referral system worked not only to recruit individuals that would be otherwise inaccessible, but it also worked in developing trust. For many participants, they regarded me as trustworthy because someone they already trusted in their lives had referred me to them. Margaret shared that she only participated in the study because her neighbor (who had been her referral contact) had reassured her I did not have a hidden “pro-technology agenda” (Margaret).

Since participants were recruited into the study by someone they trusted, they tended to trust me, as a researcher, from the start, which made them feel more at ease. The use of the dialogic method (Denzin, 2001) also helped participants feel comfortable and helped to develop our relationship.

Developing Rapport

Mary commented at the end of our sessions together, “Oh, this is just like therapy! You are so soothing to talk to and you really listen.” While active listening sought to reinterpret the meaning back to the participant (Denzin, 2001), it also resulted in participants feeling heard and we developed deep trust. Many participants shared that they had not encountered people who were interested in or open-minded when it came to their technological stories.

Older adults face many stereotypes (Glover & Branine, 1997; Longino, 2005), not only about how they think (Binstock, 2005; Cutler, 2005), but also about technology use in our societies (Cutler, 2005), including that they are slow and unwilling learners or have extremely high levels of computer anxiety (Dyck et al., 1998; Mitzner et al., 2010). Technology is stereotyped as for the young (Larsen, 1993), the young are believed to be “digital natives” (Helsper & Enyon, 2010): the valid and appropriate users of innovative new ICTs (Larsen, 1993); the old are not (Rama, De Ridder, & Bouma, 2001). Older adults often internalize these stereotypes, regardless of their skill level (Birkland, 2016).

By the end of the third interview for some participants, I was hearing painful stories which they told me that they had rarely or sometimes never shared. Margaret shared with me in our last interview that she came to see technology as slowly eroding her job responsibility. She was embarrassed to admit this, as it seemed to suggest she was overly fearful of technology in a society that worshipped it. Mindy Jean shared with me that she had little interest in using the computer and did so only to please her family members, something she would not admit to her children or husband. Natalie shared with me very personal stories about the impact of television and video games on her divorce.

Many of the participants commented that they found the study to be “fun” and “interesting” and were very keen on hearing how their case was shaping my findings. They were all eager to assist in building my theory of ICT use.

Generating a Rich Participative Theory

The notecard sort, home observations, and language checks were extremely helpful in building the ICT User Typology. The notecards, on which I had recorded the ICTs older adults were using, had abandoned and wanted to try in the future, were a powerful method of visualization. It was easy to determine an Enthusiast from their notecard sort – nearly every notecard was on display for every life context. For Practicalists, ICTs tended to only appear in one or two piles (appearing only in work or appearing only in family and community piles, for instance). Participants found using these notecards fun, with some commenting it was like a game, but it was serious enough that all participated.

By the end of the study, it was easy to distinguish the various types upon entering a person’s home. Enthusiasts’ would have their main living space enveloped in technologies; Traditionalists’ would have their television be prominently displayed; and Socializers’ would meet me at the door, cell phone in hand. Being able to observe the environment that the older adult was living in was crucial to understanding how ICTs were being used in these everyday environments.

When I showcased my ongoing results with primary participants, many had comments and suggestions, and sometimes this resulted in the generation of new stories. In developing the user type labels, I looked toward the participants’ own words, but also checked my labels with my participants themselves. I wanted to avoid the often negative, derogatory, and stereotypical labels we apply toward older adult’s ICT use. I do not believe that Traditionalists or Guardians should be portrayed negatively; both represent a legitimate approach toward technology which is just as valid as Practicalists, Socializers, or Enthusiasts. ¹⁶

Despite the power of the interpretative interactionist framework, it also had several pitfalls, including difficulty with recruiting secondary participants and challenging ethical dilemmas.

Recruitment Challenges: Secondary Participants

For some of the older adult primary participants, their networks were extremely small, making identifying and recruiting secondary participants difficult. ¹⁷ Retired older adults tended to have smaller social networks than those still working. Even if network participants could be identified, it was often difficult to track them down or arrange an interview time. June identified a list of participants I could contact, however; I was unable to get in touch with most of them and those I did contact declined to participate. Jackie did not want me to contact any of her friends in her small network: she was relying on both of them as places to park her trailer when she moved out of her apartment. (Given her precarious financial situation, she did not want to endanger her relationship with either person.)

Unfortunately, there is not much that can be done to encourage greater participation of secondary participants. While a small incentive was provided for the interview, this proved not to be effective. ¹⁸ Even when a primary participant, such as June, encouraged her contacts to return my calls, they often did not. While I had cultivated relationships with my primary participants by meeting them face to face, using the active listening techniques of the dialogic method, and meeting them several times over the course of the study, I was unable to cultivate the same types of relationships with secondary participants. These individuals were often not in the same area as myself (living at a distance) and to them, I was a voice on the phone, not a person who was meeting with them within their home. They were often less interested in the topic compared to primary participants as well.

Secondary participants were also likely concerned about contaminating their relationship with the primary participant. Some secondary participants were hesitant to speak about their relationship other than the basic “facts” of when and how they met, and how often they communicated. When I asked questions such as, “how would you describe your relationship with [the primary participant]?” some secondary participants were uncomfortable enough with the question to answer only in simple sentences and resisted further probing. Other secondary participants wanted to know exactly what I would share from the interview with the primary participant.

Given the amount of time I invested in contacting and arranging secondary interviews (which were often rescheduled at the last minute) compared to the ease of arranging primary participant interviews (with only two interviews rescheduled out of 51 total primary participant interviews), I would likely recommend not including secondary participants in such a case study, unless the focus of the study is relationships, or the potential data is predicted to be valuable.

Although secondary participant interviews did not provide data which contrasted or contradicted older adults’ own stories of their ICT use, they did yield valuable data that served to inform the ICT User Typology. When I began to develop the typology, I realized that this was not an age-specific theory, but rather that these types were reflected in the age-diverse secondary participants as well. (These data are explored in depth in Chapter 8.) While these interviews were the most difficult to collect, and these participants the most difficult to recruit, they did add value to my study. Therefore, it is important for researchers to weigh the power of the results against the hurdles in secondary participant data collection.

Sampling Diversity Challenges

As our societies not only gray, but also become more racially and ethnically diverse (Hayes-Bautista, Hsu, Perez, & Gamboa, 2002), we should not collect all white samples (Normie, 2003). Older people of color may be more sensitive to participating in research studies because of their more intimate familiarity with the research abuses their population has experienced. For older adults, racist research such as the Tuskegee Experiments (active from 1932 to 1972) (Freimuth et al., 2001) is not distant history, but rather an event that happened in their lifetimes. One cannot expect a community that experienced such horrors to be receptive to researchers, no matter the study topic. Older adults of color also tend to have fewer economic resources at their disposal compared to whites (O’Brien, Wu, & Baer, 2010), impacting their ability to participate when studies require time resources. However, from an ethical and moral standpoint, it makes the voices of these older adults incredibly important to represent.

Issues of mistrust may be lessened if the researcher is a person of color and/or already a member of that community (Freimuth et al., 2001). Gwen shared that older adults in her African American community understood that their knowledge was powerful, and many felt that sharing knowledge outside the community was relinquishing power. She suggested that in future studies having an African American individual collect such information would be helpful, as a person from within the community would face less resistance not only in entering the community, but that people would be more forthcoming and willing to share their thoughts and feelings. For white researchers, it is important to establish connections with fellow researchers who identify as people of color, who can provide vital insight. However, being or involving researchers of color is simply not enough; we must ensure our studies are ethically and professionally sound (Freimuth et al., 2001). If researchers are to have any hope of building ties with these communities, we must be diligent to ensure we treat participants fairly.

Ethical Challenges

One of the greatest challenges I encountered was that the interactionist case design often led to a blurring of the relationship between researcher and participant. Over the course of the study, the high number of contact hours and my active listening style led to several participants seeing me less as a researcher and more as a friend. This was problematic and ethically concerning: I was a researcher who was going to write about their experiences, and such writing might not always involve the flattery or omission of negative details that a friendship relationship might provide. One of the most difficult cases was Natalie.

Natalie’s situation was unique in the study: she was extremely socially isolated. The loss of her family in mid-life had been a devastating blow to her self-confidence. As a result, Natalie’s loneliness often led her to make overtures toward friendship. She would invite me to lunch and suggest we go shopping after our interview appointments. I always politely declined and gently reminded her that I was there as a researcher.

A compromise I struck with her is that I would stay an extra half an hour to speak with her at the end of each interview, but I declined going elsewhere or ordering food. She could become quite critical when I refused further socialization, which was often followed by a cycle of her apologizing for her behavior. Throughout the study, she also often contacted me with invitations to social events. I instead researched and then suggested a list of social groups she might be interested in joining focused around her political interests and hobbies. After several months, the calls dropped off.

I also observed less than ideal living situations for several of my participants. I had met Natalie at her home during the third and final interview. She had commented in previous interviews, “You can come to my house, but I have a lot of stuff.” Upon entering her home, I saw paths existed to all three downstairs doors, but otherwise, Natalie had placed items, often stacked to the ceiling, in every room of her home. I was immediately concerned for Natalie’s safety and well-being and wondered if I should intervene. As my observation continued, I examined her house for several criteria: I found that she had relatively wide paths still available in her home to three exits (and many windows were also clear and could serve as an exit if necessary) and that there was no visible garbage. The home did not smell, and even though her counters were piled with items in her kitchen and bathroom, they (as well as the sinks and toilet) were nearly spotless. The floors were also freshly cleaned, and she was currently cooking using both her stove top and oven. She had running water and electricity.

After discussion with a colleague about Natalie’s living situation, I decided that I would take no further action. While her situation was not ideal, Natalie did not express being unhappy with the way her home functioned or was organized, or even over the existence of so many objects in her living space. She commented that she, “had what she needed.”

Jackie, another participant, had fallen on difficult times after the death of her partner. The two never married because they viewed a marriage license as a “slip of paper.” Since Jackie had lived outside of the US, she did not qualify for Social Security, falling under the number of working years required to collect benefits. ¹⁹ Jackie had worked mainly hourly jobs as an administrative assistant or in retail, typically as a clerk. While her partner had left her his estate, she found she had little money left over after clearing their debts. She pieced together part-time jobs and picked up seasonal work but found it increasingly difficult to find employment. Interviewers would often comment on her age, suggesting she was unable to do the level of work required (standing, lifting, and using the checkout machines). Her work schedule was getting more difficult for her to maintain as she grew older.

Jackie had decided that she could no longer afford to maintain an apartment. She took the remainder of the estate she had inherited from her partner and bought a pull-behind popup trailer. She found a campground in the southern United States that only charged US$50 a week to park a trailer, and she planned to move to the campground for nine months of the year, returning north to live on her friends’ property during the summer months. She had several leads on retail jobs in the area she was moving to, convinced that US$200 a month in “rent” would be much more affordable than the US$800 she was paying for her current apartment. In the end, I realized that although I could suggest that Jackie look into social welfare programs, there was little I could do to help.

Encountering these situations in the field was challenging for me personally. What I found to be of great help was to develop a network of colleagues who were also researching older adults or other at-risk communities. Within this network, I could discuss the issues I was facing in my research, talk through my thinking, and bounce ideas and solutions off my colleagues. I was not alone, and I was not the only person experiencing ethical dilemmas and encountering challenging situations.

To any researcher working with older adults, or indeed with any at-risk population, developing such a network of colleagues is essential. In the end, unless there is a case of abuse observed, it is up to the researcher to determine their limits and when they will intervene, and how. Using such a group to talk through such issues (always keeping the identity of participants secret) can be helpful not only in determining solutions, but also in helping the researcher to deal with their own difficult emotions.

When it comes to these ethical issues highlighted when working with older adults, it is important to set boundaries, but it is also important to be flexible and understanding of your own personal limitations. Things will likely change as your study progresses, and you will likely encounter situations one would not expect. It was impossible to not feel heartbroken at Natalie’s situation or to be concerned about Jackie’s. While it is important to be kind to your participants, it is also important to remember to be kind to yourself.

I wish to end this book the way I started it, by acknowledging the older adult participants who made such a study possible: thank you for sharing your lives with me and for helping me to develop the ICT User Typology. The two years I spent in close contact with you will forever be a highlight of my life, professionally and personally. Thank you for your stories!