Social Cognitive Theory, Driving Cessation, and Alternative Transportation in Later Life

Abstract

Having viable alternative transportation options could help individuals stop driving when appropriate. This study employs the Social Cognitive Theory (SCT) to understand the barriers and facilitators of alternative transportation among a sample of adults aged 55 and older (N = 32). Using a daily transportation data collection app, MyAmble, the research team asked participants questions structured around environmental, individual, and behavioral factors as outlined in the SCT framework. Responses were analyzed using directed content analysis. Findings suggest a substantial reliance on motor vehicles and it was evident that many participants had never seriously considered what they would do if they could no longer drive. We posit that SCT principles may be applied to help older adults build self-efficacy to transition to driving cessation when needed.

What this paper adds

• • SCT is not only a means of understanding behavior but also a powerful tool for designing assessment and interventions related to alternative transportation in later life.

Applications of study findings

• • SCT principles may be applied to help adults (age 55 and older) build self-efficacy to transition to driving cessation when needed.

Background

As adults age, many drive and remain mobile by driving; however, not everyone drives in later life and many older adults reduce or give up driving (Chihuri et al., 2016). On average, adults (age 65) and older outlive their ability to drive by 7 years (Foley et al., 2002). Identifying ways to increase the use of alternative transportation (e.g., bus, walking, biking) options by older adults is needed as the number and percentage of older adults increases across the United States. Expanded use of alternative transportation may allow older adults to meet their daily needs and stay socially connected while also supporting their health and independent mobility.

Social Cognitive Theory and Driving Cessation

Social cognitive theory (SCT) (Bandura, 1986) is a theory of human behavior that suggests that individuals are shaped by a reciprocal interaction between environmental, individual, and behavioral factors. SCT is considered a fundamental framework to explain domains of human behavior and behavior change (Luszczynka & Schwarzer, 2020). SCT has been used in studies of transportation behavior related to older adults with visual impairment (Crudden et al., 2016) and older adults transitioning to public transit (Ravensbergen et al., 2022).

Using the SCT framework, older adults’ experiences with transitioning from drivers to non-drivers are shaped by environmental, individual, and behavioral factors. In order to promote and increase the utilization of alternative transportation, it is important to take into consideration these three factors. Because there is a dependence on personal vehicles in the U.S. to meet transportation needs, it is important to recognize the role of self-efficacy to build knowledge, skills, and ultimately change transportation behavior in response to individual mobility needs and environmental options (Windsor & Anstey, 2006). Self-efficacy is an individual’s perception or belief in their own abilities which in turn influences their behaviors and actions (Bandura, 1994).

Transportation self-efficacy is “one’s belief that they can successfully get where they want to go, or otherwise complete transportation tasks” (Cochran, 2020, p. 2). Research by Cochran (2020) suggested that feelings of low self-efficacy may limit travel among adults who had recently acquired disabilities and who had less training/experience using transportation with a disability (Cochran, 2020). Furthermore, Ravensberger and colleagues (2022) found that self-efficacy influenced the transition to public transit use among older adults. In the context of alternative transportation, an individual with high self-efficacy may be more likely to consider taking the bus, walking, or biking to their destination. Because self-efficacy is situation specific (Bandura, 1977), transportation behaviors will vary depending on type of alternative transportation.

Environmental Options

Environmental factors affect individuals’ ability to utilize alternative modes of transportation. For example, rural older adults are twice as likely to indicate that driving cessation would have a high impact on their daily lives (Hansen et al., 2020; Strogatz et al., 2019). Rural older adults are particularly at risk for social isolation upon driving cessation (Hansen et al., 2020). Older adults benefit from public transportation and mobility supports (Ang et al., 2019); however, those in rural areas are vulnerable to negative health and social outcomes after they stop driving because neither public transportation nor active transportation tools are readily available (Hansen et al., 2020).

Features of the built environment, such as curb ramps, lighting, street crossings, sidewalks, covered/sheltered areas, level/flat ground, and low traffic roads, are key for mobility and physical activity in mid to later life (Rosenberg et al., 2013). Characteristics of the built environment impact how older adults travel, including walking, biking, and taking public transit (Loukaitou-Sideris et al., 2019). Using data from the National Household Travel Survey, Yang and colleagues (2018) found that older adults in the most supportive built environment were four times more likely to use public transportation than the older adults as whole.

Individual Ability and Need

Older adults assess their ability to continue driving based on their functional and health status (Anstey et al., 2017) as well as based on recommendations from their physician and family/friends (Hassan et al., 2022). Reduced processing speed, difficulty reading maps, older age, and poorer self-rated health are associated with a shorter expectancy of driving years left among older adults (Anstey et al., 2017). Shorter self-rated driving expectancy also predicts future driving cessation (Anstey et al., 2017). Additionally, older adults’ evaluation of their driving skills can be influenced by major incidents, such as being in a collision or narrowly missing a collision; minor challenges with driving, including difficulty with parking; and caregivers’ assessment of older adults’ driving skills (Ang et al., 2019). Age-based stereotypes and driving anxiety can also negatively influence older adults’ driving confidence and decisions for driving cessation (Taylor et al., 2018). Expectations for years left to drive vary greatly among older adults (Babulal et al., 2019).

Behavioral Patterns

A constellation of factors is related to driving cessation including health changes, cognitive ability, and previous driving experience (Schouten et al., 2022). Older adults that are at increased risk for driving cessation (e.g., those with lower income, females, and racial and ethnic minority older adults) plan for driving retirement more than their counterparts (Vivoda et al., 2021). Drivers who find driving stressful, who have lower driving confidence, and view driving alternatives more positively are more likely to plan for driving retirement (Vivoda et al., 2021). Social networks also play an important role in the driving reduction and cessation among older adults. When perceiving a need to regulate their driving, older adults often share driving responsibilities with their spouse (Ang et al., 2019). Informal transportation support from one’s social network plays an important role in mobility after driving cessation (Choi et al., 2012).

Research Design and Methods

This study was a part of a larger study to understand how community residents (age 55 and older) use transportation, identify facilitators, and barriers related to transportation use by residents, provide evidence-informed recommendations to increase access and use of alternative transportation. As part of the parent study, the research team used a daily transportation app, MyAmble, whose purpose is to collect data relating to individuals’ transportation habits and patterns (Fields et al., 2022). Key features of the app and type of data collected are outlined in Table 1. The app utilizes an ecological momentary assessment design (EMA) in order to collect data in the lived, “real world” of the participants and to focus on the participant in their current state versus asking them to recall information (Shiffman et al., 2008).

Table 1.

MyAmble Comparison to Other Transportation Data Collection Strategies.

Features/Data	Paper/Website Travel Diary	Smartphone Travel Diary App	MyAmble	Objective or Subjective
Observed Trips
*Mode	X	X	X	O
*Purpose	X	X	X	O
*Departure time	X	X	X	O
*Origin/destination	X	X	X	O
*Trip importance		X	X	S
*Trip success		X	X	S
*Trip challenges			X	S/O
*Impact on mood		X	X	S
*Interact w/friends/family		X	X	S
Unserved/failed Trips
*Purpose			X	O
*Trip importance			X	S
*Impact on mood			X	S
*Reason for no trip			X	O
*Consequences			X	S/O
GPS identifies trips		X		O
GPS verification of destination		X	X	O
Social exclusion and transportation			X	S/O
Travel History			X	S
Visual record of challenges		X	X	S/O

Travel Buddy

The focus of the current study are the findings from the interactive Travel Buddy feature of MyAmble. Travel Buddy provides real-time, daily, qualitative data collection in a naturalistic setting (i.e., EMA design) (Fields et al., 2019, 2021; Stone et al., 2007). The Travel Buddy was designed using an EMA approach as it is the dynamic (i.e., daily text messaging) versus static (i.e., survey/interview) data collection feature of MyAmble. Research suggests that text messaging, including with older adults, is a feasible method for researchers to rapidly collect rich textual data (Redlich-Amirav & Higginbottom, 2014; Twis et al., 2020). The text-messaging in the Travel Buddy feature allows participants to have a semi-structured conversation every day of the 14-day study period with members of the research team. At least one question was sent to each participant per day by their assigned Travel Buddy. In line with EMA methods, the day and times of the messages varied. Participants are invited to type or use the voice to text option to create their messages. The research team designed questions for participants to qualitatively share their transportation experiences related to the domains of SCT (Bandura, 1986) (see Table 2 for the domains and their corresponding questions).

Table 2.

Travel Buddy Questions Across the Domains of Social Cognitive Theory.

Environmental	Please tell me about your community…what is it like to live where you live?
	What about your community makes it difficult to get around?
	What about your community makes it easy to get around? (Probes – walking, biking, bus)
Individual	How do you get “out and about?”
	What do you need in order to walk more frequently?
	What do you need in order to ride the bus more frequently?
	What do you need in order to ride a bike more frequently?
	Tell me about going places with others
	Tell me about going places by yourself
Behavioral	How could you change the way that you “get out and about?”
	What do you need to do in order to walk more?
	What do you need to do in order to ride the bus more?
	What do you need to do in order to ride a bike?

Sample

Thirty-two participants were recruited across three communities in Franklin County, Ohio to document their travel patterns for a two-week period using the application MyAmble. This study received approval from the University Institutional Review Board (IRB#: 2019B0150). The communities were purposefully selected to reflect urban, suburban, and rural areas in the County. Specific inclusion criteria included English-speaking adults ages 55 and older who live, work, or travel in the target communities, and had the cognitive ability to provide informed voluntary consent. The age cut-off of 55 and older was selected because some individuals may experience age-related health changes earlier than others due, for example, to the negative impacts of poverty and discrimination. Participants were recruited through community engagement efforts related to this project. The study team visited popular community “hubs” such as senior centers, community centers, and housing developments, in order to engage directly with older adults, inform them of the study, and solicit their feedback on the study process. The final sample included 12 older adults from a rural area, 11 from an urban area, and 9 from a suburban area.

The age of participants ranged from 56 to 88 years old, with an average age of 69.65 and the majority of participants were aged 60 and older (6.45% < 50; 48.38% = 60–69; 35.48% = 70–79; 9.67% > 80). There were 11 males (34.40%) and 21 females (65.60%). The majority of participants were White (n = 19, 59.40%), 10 were Black (31.30%), 2 were Asian (6.30%), and 1 participant identified as being two or more races (3.10%). All participants identified English as their primary language. In terms of education, 12.5% (n = 4) of the sample received a high school-level education or less, 31.20% (n = 10) completed some college and/or a technical degree, and 53.10% (n = 17) received a Bachelor’s degree or higher. Seventeen participants (53.10%) were married at the time of the study, and 14 (43.80%) were either single, divorced, or widowed. Twenty-four (75%) participants reported living in their own homes. Almost 44% of participants (n = 14) reported living alone, and 56.20% (n = 18) reported living with others. Just over 28% (n = 9) had been living at their current residence for fewer than five years, and 68.70% (n = 22) had been living at their current residence for five or more years. Over 80% of participants accessed the internet from home on a daily basis and 48% of participants reported using a combination of a computer/laptop, tablet, and phone. Finally, 88% of the sample still drove a personal vehicle.

MyAmble Data Collection

After consenting to the study, participants in each community attended a training event where they were assigned a “Travel Buddy,” and were given training materials as well as a Samsung Galaxy Tab A 8 inch tablet enabled with a three-month wireless data plan. Data collection using MyAmble occurred in October and November of 2019. Five research team members were paired with five to eight participants each. The research team engaged their “Travel Buddy” at least once a day during each community’s 14-day study period. The Travel Buddy questions (see Table 2) were asked across the 14 days, typically with one question per day.

Data Analysis

All data were stored in a cloud-based interface and extracted into a secure MyAmble database. Results were exported into Excel and then copied into Microsoft Word. Figure 1 illustrates how the SCT framed the analysis for this study. Three members of the research team used directed content analysis (Hsieh & Shannon, 2005) and iterative coding to move from codes to themes (Strauss & Corbin, 1998). Based on the study’s research questions, the research team began by using barriers and facilitators as initial coding categories (Potter & Levine-Donnerstein, 1999). First, three team members independently coded 25% of the transcripts. Next, the team members met virtually several times to discuss the codes and to establish consensus by discussing any differences until an agreement was met for each code. If agreement could not be reached, another research team member was available to resolve conflicts, however, this was not needed. Once consensus was reached, all of the transcripts were imported into NVivo 12, a qualitative data analysis software. Following this step, one researcher member then coded the remaining 75% of the transcripts based on the coding scheme. These transcripts and codes were then checked and refined in NVivo by the other two team members. The codes were then grouped into categories and finally into overarching themes. Lastly, the themes were mapped onto the domains of the SCT by two of the researchers which were then reviewed by the entire research team. (see Supplementary Table 3 for theme definitions and example quotes). Rigor was enhanced through peer-debriefing during the coding and theming (Lincoln & Guba, 1985) as well as through triangulation using multiple data analysts (Patton, 1999).

Figure 1.

Application of social cognitive theory to driving cessation and alternative transportation to the data analysis.

Results

Analysis of the data revealed 19 themes reflecting barriers and facilitators of alternative transportation, barriers to driving, and looking ahead to driving cessation. Themes reflected environmental, individual, and behavioral factors influencing alternative transportation use as suggested by SCT and are presented below. Please note that these quotations are taken word for word from the text message conversations and may include typos and other errors. Street names have been blinded to protect potentially identifiable information.

Environmental Options

Many of the Travel Buddy conversations centered on environmental factors and how they contributed to participants’ ability to use transportation. There was a strong emphasis on how the environment hinders transportation, particularly alternative transportation. Seven themes emerged as environmental barriers to alternative transportation: Safety, Proximity to Destinations, Bus Logistics, Weather, Sidewalks, Active Construction, and Needed Construction.

Barriers

Participants shared that their communities often did not provide safe options for alternative transportation. One participant stated, “I associate the bus, with criminals riding the bus, then getting off and robbing or hurting someone. Then, how far would I have to walk to my final destination.” Another participant articulated similar concerns about safety: “I am capable of driving most places. As long as I am capable of driving, I don`t think I would ride the bus. I just don’t think I would feel comfortable riding the bus for some reason it just does not feel safe or warm.” Another participant noted, “I always drive. And if I am meeting someone we drive separately. Would not consider public transportation. Nor [Lyft] which I don’t feel is safe. Just my opinion.”

Proximity to destinations and bus logistics were reported as a barrier to alternative transportation. One participant shared that there was “No grocery or doctor within walking distance.”

Another participant cited challenges with public buses:

It is approximately 5 miles to the closest one on X street and about the same to the closest one on X Road. Not exactly a good mode of transportation for those of us in a more rural area. Driving a car or at least riding in one is the most convenient and practical way to travel out here.

Another participant reported that “the nearest bus line that I am aware of is practically three and a half miles away. So if you do not have access to a car you really can’t get much done. Even the nearest stores are two miles away.”

Weather emerged as a barrier-related theme. One participant shared, “Not sure I’d ride the bus as long as I can still drive myself. Standing out in the weather and walking to and from bus stops is not appealing.” Similarly, another participant reported, “I won’t be standing in the heat or cold to wait for bus to go to the grocery store. We would have to have much better transit system before I can see myself using the bus on a regular basis.” Additionally, as it relates to walking as alternative transportation, one participant stated that “the weather changes its either cold or rainy that changes my plan of walking more.”

Other environmental barriers included sidewalks and construction. For example, one participant reported “there are no sidewalks in my immediate neighborhood. And really there is no place to walk to from our home.” Another person shared, “There are no sidewalks, roadway is busy, and there is no berm to speak of. Even if you make it over to the strip mall, the parking lot is full of pot holes.” Related to active construction, one participant shared:

It is definitely a problem with mobility in my community because of all the construction that’s going on both underground with sewer pipelines as well as Road and Street construction. Paving, repaving, and now additionally with renovations, remodeling, tear down houses, and various property issues because this regentrification is going on.

Two themes emerged that described the environmental factors that may hinder participants’ ability to continue to drive: Infrastructure and Traffic. When describing how community infrastructure makes driving more difficult, one participant wrote, “Yes, we have to rely on car travel. The roads are all two-lane with deep ditches on each side with rural 55 mile and hour speeds. It definitely adds to the congestion.” Another participant shared:

For me the X [highway] and the X [highway] are death traps – in particular the X [highway]. I have recently been introduced to an eight lane-yes eight lane highway to get to the [mall] shopping experience place. Listening to the news in the morning freaks me out. I do not remember a day without an accident – even in clear beautiful weather.

Although many participants noted environmental factors as barriers to alternative transportation, some participants reported environmental facilitators that made it easier or more convenient for them to “get around” including Sidewalks/Walkability, Bus Logistics, and Weather.

Facilitators

One participant discussed their community in terms of walkability and convenience for alternative transportation: “I am fortunate to be able to live sufficiently close to many locations I can either walk or bike to. I can drive or ride to those places farther away.” Similarly, a participant shared “we have sidewalks, we’re close to the bus, the freeway and the airport.” Another participant noted:

We are a small housing development build in the fifties. The streets are short, there are three thru-ways to get to the main streets. We are sort of a circle connecting to each other. So that it’s easy to walk, bike or run around the neighborhood.

Related to bus logistics, one participant stated, “There are frequent public busses in our area.” Weather was also mentioned by participants as a facilitator of alternative transportation: “walking when the weather is ok, and biking when the weather is nice” and “in theory we could walk in good weather.”

Individual Ability and Needs

Many participants described their ability (or inability) to use alternative transportation instead of driving in terms of their own physical abilities. One theme arose from the data relating to participants’ Personal/Physical Factors being a barrier to alternative transportation.

Barriers

One participant wrote, “Because of my limited physical abilities to walk and be mobile I do not ride the bus or any form of public transportation.” Similarly, one participant shared, “for the last several years I’ve had a work-related injury that has prohibited my ability to walk long distance I’ve had two knee surgeries and now I’m being scheduled for a total knee replacement hopefully that will be approved for this month in November later in the month but because of these medical challenges it’s very difficult for me to do any type of extensive walking.”

When asked about riding the bus, another participant responded, “I would have to be incapable to drive because you have to walk several blocks to a bus stop.” When asked about biking, another participant shared, “I don’t think it’s [biking] safe for me. As I said, I have asthma. even though it’s well controlled for the most part, I am allergic to almost all tree pollens.”

Personal/Physical Factors hindered not only alternative transportation use, but also driving ability. During a Travel Buddy exchange, one participant discussed a diminished ability to drive: “I like to just drive if I go but probably I would say nearly half the time I won’t go places so that’s what spirals me into depression because I can’t go because of my medical limitations and [if] I ride with somebody else and I’m not feeling well I feel stuck.” Medical limitations were also cited as a barrier by another participant: “I don’t have a car and I have to have somebody else take me because I’m going blind in my right eye so I’m under somebody else’s care.” One other participant stated that his or her main obstacle to driving was “having difficulty remembering locations.”

Behavioral Patterns of use

Many of the Travel Buddy participants reported driving as their primary and preferred mode of transportation. For example, one participant shared, “I have always driven It defines me. I can’t see myself taking public transportation.” Similarly, another participant reported, “I like to be a passenger. I like the independence of being able to drive myself places. [Typically], other than going places with my husband, I usually drive myself wherever I need to go.” However, four themes emerged from Travel Buddy data which fell under the Behavioral domain of the SCT. All four of these themes involved participants “looking ahead” and describing how they would get to where they need to go if they could no longer drive. These four themes were Walk, Ride the Bus, Rely on Others, and Use Uber and/or Lyft. For example, one participant shared: “if I couldn’t drive, I would walk or ride the bus.” Another participant stated, “I would need to rely on others, such as friends or family.” Uber and Lyft were also reported as potential alternatives to driving. One participant reported, “I could take Uber or Lyft, or call a friend.”

Despite this future-oriented thinking, however, some participants expressed reservations or anticipated complications of no longer being able to drive. As one participant stated, “I suppose I would have to rely on family or friends, however, I would hate to be an imposition. I think that for some people using [Uber] or [Lyft] would be a [plausible] solution to that problem, however I honestly would be wary of getting into a vehicle with an unknown person.” Ridesharing services also came up in conversation with another participant in the same community: “if I was not able to drive and did not want to move, I guess I would try Uber or Lyft since COTA [bus] does not come closer than 1.1 mile. [It] is not safe to walk on X Street/US X.” One other participant said, “I could take the bus more places rather than driving myself, I do lack confidence in terms of finding my way.”

Discussion and Implications

Within the framework of the SCT, this study qualitatively explored participant experiences with transportation using Travel Buddy, the qualitative feature of MyAmble. The application of the SCT provided the opportunity to recognize the environmental, individual, and behavioral influences on self-efficacy relating to driving cessation and alternative transportation use among a sample of adults aged 55 years and older in Central Ohio.

Overall, participants indicated a preference for driving. These findings are not surprising, as most daily trips completed by adults aged 65 and older in the United States are by driving a privately owned vehicle (Shen et al., 2017) and driving is viewed as key to their independence (Luiu et al., 2017). For many participants in this study, driving provided a sense of autonomy and independence. Participants also expressed little planning for driving cessation. These findings are consistent with previous research indicating that older drivers (ages 53–92) had done little to no planning for future transportation needs or for a future without driving (Harmon et al., 2018).

However, after using MyAmble, many participants in the study recognized a need to plan for their future.

Consistent with previous research (Van Cauwenberg et al., 2012), participants reported barriers to alternative transportation use including concerns about safety, proximity to destinations, weather, and construction. Participants also shared that alternative transportation options, such as buses, were difficult to access due to proximity, logistics, and scheduling. These findings are aligned with other research suggesting that older adults in the U.S. consider inconvenience, safety, and the expense of buses as barriers to using them for their travel needs (Jones et al., 2018). Participants further indicated that the built environment, including sidewalks, were an environmental facilitator (or in some cases, barrier) to alternative transportation. In another study in Central Ohio, sidewalks were cited as playing a significant role in the mobility of older adults (Cao et al., 2020). Sidewalks also impact older adults’ neighborhood participation (Twardzik et al., 2021). Together, these findings point toward the need for improvements in the infrastructure and built environment as key environmental components to increasing older adults’ use of alternative transportation. However, within the SCT, there is a recognition that the environment alone is not sufficient to explain alternative transportation barriers and facilitators among older adults. The SCT also considers the individual and behavioral factors that influence the environment when considering issues of transportation and mobility among older adults.

Related to the individual factors of the SCT, participants in the study reported personal/physical barriers to using alternative transportation. These findings are consistent with previous research suggesting that sensory, cognitive, and physical impairments affect older pedestrians (Tournier et al., 2016). For example, the inability to walk long distances impacted using the bus, particularly if bus stops were too far away. Some individual barriers speak to the need to further explore innovative door-to-door alternative transportation options as well as the need to address first and last mile accessibility. However, personal/physical barriers to using alternative transportation may not be insurmountable if transportation self-efficacy is strengthened. In a study of mobility among adults with disabilities, individuals who were more comfortable asking for help from others and who had developed higher transportation self-efficacy by relying on others made travel easier and opened up more opportunities for making trips (Cochran, 2020). Cochran and colleagues (2020) also found that older adults with recently acquired disabilities were able to learn travel skills and build transportation self-efficacy by relying on social service providers and other people with similar disabilities.

In line with the SCT and the behavior domain, participants suggested that they had not considered their future without a car. These findings point toward low levels of planning around driving cessation. According to many of the participants in our sample, driving is virtually the only form of transportation that they perceived as viable. However, they also perceived driving as unsafe. This reflects the core problem of older adults continuing to drive despite understanding that driving tends to become more dangerous with age. Considering the heavy reliance on cars as the primary mode of transportation for most of our participants, it is evident that more work needs to be done to help older adults plan for their future when driving is no longer an option.

Findings from this study underscore that to increase alternative transportation self-efficacy, intervention strategies should incorporate individual ability and needs, behavioral patterns of use, and environmental options. For example, among Federal Highway Administration’s proven safety countermeasures for pedestrians to safely cross a roadway is installing a median or refuge island that allows pedestrians to cross one direction of traffic at a time (U.S. Department of Transportation, n.d.). This evidence-based strategy combined with the use of MyAmble to initiate proactive thoughts about driving cessation (individual) and peer-based travel trainings (behavioral) may support walking as an alternative transportation option.

Limitations

Study findings should be interpreted with caution as several limitations exist. First, study findings are not generalizable as the sample was modest and limited to a particular geographical area. Next, the Travel Buddy findings tended to elicit barriers. This could be due to the manner in which questions were worded (e.g., “What do you need to do in order to walk more?”), or the way the study team tended to use probing follow-up questions. It could also be that this sample did in fact perceive more barriers than facilitators. Future studies could be more intentional to strike a balance between probing about barriers and probing about facilitators. Finally, Central Ohio is home to a racially and ethnically diverse population of older adults. Future studies with a larger and broader sample are warranted as it is important that alternative transportation options meet the needs of diverse older adults (Jones et al., 2018; Kerschner & Silverstein, 2018).

Conclusion

Social Cognitive Theory is not only a means of understanding behavior but also a powerful tool for designing interventions with older adults. If we use SCT as a lens through which to understand older adult transportation behaviors, we can come closer to understanding which interventions work under which circumstances and for whom. Recognizing the three domains of the SCT, and the unique individual and community factors present, provides the opportunity for person-centered and community-focused interventions to support driving cessation and alternative transportation utilization.

ORCID iDs

Noelle L. Fields https://orcid.org/0000-0002-0211-6037

Qiuchang Cao https://orcid.org/0000-0003-0461-4731

Alan Kunz-Lomelin https://orcid.org/0000-0003-3423-6137