Barriers to Developing and Sustaining Driving and Community Mobility Programs

Wendy Stav; Laura Snider Weidley; Anthea Love

doi:10.5014/ajot.2011.002097

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Research Article | July 2011

Barriers to Developing and Sustaining Driving and Community Mobility Programs

Wendy Stav; Laura Snider Weidley; Anthea Love

Author Affiliations

Article Information

American Journal of Occupational Therapy, July/August 2011, Vol. 65, e38-e45. doi:10.5014/ajot.2011.002097

Abstract

OBJECTIVE. To begin to address the shortage of driving rehabilitation and community mobility programs to meet the community mobility needs of older adults and clients with rehabilitative needs, we sought to identify the key barriers to developing and sustaining such programs.

METHOD. We used a survey design to solicit input from a nationally representative sample of occupational therapy practitioners, rehabilitation managers, and health care administrators.

RESULTS. The 2,869 completed surveys revealed widespread and largely contextual barriers related to fiscal support, infrastructure, physical environment, and institutional culture. The barriers were highly correlated with each other and did not differ across regions, practitioner experience levels, or facility types.

CONCLUSION. This study was an important preliminary step in constructing a resource toolkit with strategies to overcome the identified barriers to developing and sustaining driving and community mobility programs that meet the needs of older adults and clients with rehabilitative needs. This toolkit, which is available on the American Occupational Therapy Association’s Web site, is a necessary resource for use in all practice settings to meet the driving and community mobility needs of this population in support of engagement in community-based occupations.

Occupational therapy recognizes that optimal functioning and independence in areas of occupation contribute to health, well-being, and quality of life for individuals, organizations, and populations. Specifically, occupational therapy addresses activities of daily living (ADLs), which include tasks related to self-care, and instrumental activities of daily living (IADLs), which facilitate complex interactions between the client and the environment (American Occupational Therapy Association [AOTA], 2008). Community mobility, one of the identified IADLs, is defined as “moving around in the community and using public or private transportation, such as driving, walking, bicycling, or accessing and riding in buses, taxi cabs, or other transportation systems” (AOTA, 2008, p. 631). Availability of services to address the driving and community mobility needs of the population is limited; the focus of this study is the investigation of barriers that limit these services.

Driving and community mobility is an area of occupation that has great significance for many different people, especially older adults. Research has shown that older adults associate a sense of freedom and independence with driving and community mobility (Gardezi et al., 2006). When driving is no longer possible or the ability to engage in community mobility is compromised, people feel stripped of their freedom and independence. Driving is an integral part of daily life for older adults because it allows them to feel connected to the larger community by participating in everyday life activities (AOTA, 2010a).

Although driving and community mobility is identified as an area of occupation, it is also an occupation enabler because it contributes to engagement in other areas of occupation (AOTA, 2010a); it enables access to health care, promotes and maintains social participation, allows for maintaining one’s daily life routines, allows for traveling and shopping, enables participation in leisure activities and work, and facilitates fulfillment in the role of caregiver. The ability to drive also fosters a sense of control over one’s life because of the convenience, flexibility, and spontaneity associated with driving (Gardezi et al., 2006).

The importance of driving for older adults is further highlighted in the literature, which demonstrates evidence of social isolation and subsequent increases in depressive symptoms after driving cessation (Carr, Duchek, Meuser, & Morris, 2006; Marottoli et al., 1997). Many older adults avoid the idea of driving cessation for various reasons (Gardezi et al., 2006), but all mature drivers are encouraged to plan for it (Bauer, Adler, Kuskowski, & Rottunda, 2003) to ensure that they are able to continue participating in everyday life activities after cessation. Researchers have discovered that although older adults may need to stop driving, many do not because they do not have suitable transportation alternatives, such as available friends or family or accessible and dependable public transportation (Bauer et al., 2003; O’Neill, Bruce, Kirby, & Lawlor, 2000). For this reason, it is critically important that programs and services be available to support the continued driving of older adults and promote transportation alternatives for those who can no longer drive.

Literature Review

Age-related conditions may result in difficulties in driving performance and safety (Carr, 2000), reflected in increased crash, injury, and fatality rates among the older adult population. Although it is true that age-related conditions and health changes may affect a person’s functional capabilities, age should not be the sole determinant of driving ability because of the vast differences in both health and ability among older adults (Odenheimer, 2006). Rather, drivers’ ability to continue driving should be determined by an evaluation of their driving performance and safety, not by age or diagnosis.

The crash, injury, and fatality data from 2008 reveal that older drivers, compared with their younger counterparts, were overrepresented in crash-related injuries and fatalities in a per-mile-driven comparison. This finding is consistent with the existing trend of overrepresentation of older drivers in crash-related injuries and fatalities. The disparate crash rates are attributed to both driver performance and frailty and fragility issues (Eberhard, 2008). In 2008, older drivers accounted for 8% (183,000) of traffic-related injuries and 14% (3,458) of traffic-related fatalities (National Highway Traffic Safety Administration [NHTSA], 2009). These values are expected to remain the same or increase, because 31 million licensed drivers are over age 65, and an increase is expected as the aging population grows (NHTSA, 2009). Negative crash outcomes are a concern to federal agencies such as the Centers for Disease Control and Prevention (CDC), which included in Healthy People 2010 a national driver safety goal to reduce the rate of deaths due to accidents to no more than 8 per 100,000 people (CDC, 2007). This goal has yet to be accomplished; for the past decade, the death rate for older adults has been 23 per 100,000 (CDC, 2007). The U.S. Government Accountability Office (2007) noted, “Efforts to build safer roads and develop better methods of assessing driver fitness are keys to helping older people continue to drive safely and maintain their mobility, independence, and health” (p. 1).

According to the AOTA “Find a Driving Specialist” database, only 264 driving programs across the United States are available to serve the 31 million identified licensed older drivers (AOTA, 2010b). The number of programs seems to be declining since a study published in 2006 using the same database found 510 programs (Stav, Justiss, Belchior, & Lanford, 2006). Not every older driver will require driving rehabilitation services, but the availability of 1 driving program for every 117,424 older drivers is insufficient. The number of programs continues to decline: More than 100 fewer programs were listed in the database between the dates of our study and the writing of this article. The diminishing number of programs is significant to the aging driver population but also to younger drivers because these programs and resources also serve the driving and community mobility needs of younger adults with disabilities, including those who have sustained traumatic brain injuries, spinal cord injuries, amputations, or other disabling conditions.

Not enough has been done to make occupational therapy services easily accessible to older adults or other drivers in need of driving rehabilitation or community mobility services. It is imperative to discover the barriers health care and community facilities face in developing and sustaining driving rehabilitation programs to begin to develop pathways to overcome those barriers. Both the establishment of more driving rehabilitation and community mobility programs (Granda & Thompson, 2006) and the continuation of existing programs are necessary.

In the study described in this article, we sought to identify the key barriers to developing and sustaining driving and community mobility programs that meet the needs of older adults and other drivers. This study was the first phase of a larger project that resulted in the creation of a resource toolkit to overcome these barriers. (The resource toolkit is available to occupational therapy practitioners and health care administrators nationwide at www.aota.org/Older-Driver/Professionals/Toolkit/Programs.aspx.) We aimed to answer the following questions during this scientific inquiry:

What barriers do rehabilitation managers, health care administrators, and occupational therapists encounter when working with program development?
What are the real versus perceived barriers acknowledged by the occupational therapist, health care administrators, and rehabilitation managers?
What roles does geographic location play in hindering driving and community mobility program development?

Method

Research Design

This survey was designed to identify the perspectives of health care providers related to their experiences with driving rehabilitation and community mobility program development. A survey design was chosen for efficiency, cost-effectiveness, and ability to capture the broadest range of perspectives of health care providers nationwide.

Participant Selection

The settings for this study encompassed health care facilities and community-based organizations in the United States. The personnel in these settings included a variety of health care providers, but this study targeted three different levels of providers: occupational therapy practitioners, rehabilitation managers, and health care administrators. Respondents in each group were identified through databases. The occupational therapy practitioners were identified through the AOTA member database. A cluster sampling technique was used to target AOTA members by their membership in the Physical Disabilities, Home and Community Health, Gerontology, and Technology Special Interest Sections and the Driving and Driver Rehabilitation Network. After cross-checking and removal of duplicate names, 14,990 occupational therapy practitioners were invited to participate in the study.

The rehabilitation manager group in the sample was identified through two sources: AOTA’s Administration and Management Special Interest Section member list, which included 5,255 occupational therapy practitioners, and the e-mail distribution list for Rehab Management Magazine, which included 8,500 names. The health care administrator participants were identified from a list of 1,400 members accredited by or associated with the Commission on Accreditation for Rehabilitation Facilities (CARF); CARF members work for rehabilitation agencies in both inpatient and outpatient facilities.

In addition, 55 people were identified from a list offered by the California Board of Occupational Therapy that included names and e-mail addresses of people interested in occupational therapy practice and licensure wishing to be informed about meetings and licensure changes. State licensure boards were contacted to invite professionals who were not members of AOTA, but no state in the country that had a database with e-mail addresses was willing to sell the information.

Instrument

A data collection instrument was created for use in this study. The development process began with a review of the literature for studies that examined barriers in health program development worldwide and across a variety of disciplines. From relevant literature, we conducted a content analysis and identified common barriers. We then transformed the identified barriers into questions that formed the bulk of the data collection instrument. We completed a draft of the instrument by adding questions about respondent demographics, work setting, and experience with program development. The development process continued through several drafts and three separate content review phases by 15 reviewers with expertise in one or more of the following areas: health care administration, health care financing, questionnaire development, the driving and community mobility practice area, and community practice with older adults.

Procedures

Participants were invited to complete the Web-based survey via an e-mail that provided a direct link to the survey and were given 4 wk to complete it. A reminder e-mail was sent 2 wk after the initial invitation. Additional solicitation for participation was published on the AOTA 1-Minute Update, which is a biweekly online newsletter distributed to the AOTA membership via e-mail. Anonymous responses to the questions were electronically transferred from the data collection software into a secure database maintained by AWP Research (Herndon, VA), the questionnaire company that held the contract for this study. Study participants willing to be contacted at a future date for follow-up questions provided their personal contact information on a completely voluntary basis.

Analysis

We examined the demographic data to identify descriptive statistics and frequency data for the barriers to determine their prevalence. Cross-tabulations with Cramer’s V were used to identify correlations among the barriers and practitioner experience level, facility type, region of the country, decision-making control, and program development experience. Additionally, we conducted between-barrier correlation analyses to see whether relationships existed that could be helpful in the creation of the resource toolkit. All statistical calculations were performed using SPSS 15.0 (SPSS, Inc., Chicago).

Results

A total of 24,945 respondents were asked to participate in this study. From that population, 3,191 individuals responded, representing a response rate of 12.8%. After cleaning the data and removing insufficiently completed surveys, we included 2,869 participants in the final analyses. Most participants (94.6%, n = 2,715) came from the AOTA Special Interest Section distribution lists; the rest included 2.9% (n = 84) who responded to an invitation on AOTA’s 1-Minute Update, 1.6% (46) who responded from the CARF member list, and 0.8% (n = 24) who responded from the Rehab Management Magazine distribution list. The sample consisted of 2,094 occupational therapy practitioners (72.9%), 517 (18.0%) managers, and 258 (8.9%) administrators. A substantial portion of the sample (n = 746, 26.0%) had >25 yr of experience working in a health care field; 57.9% (n = 1,664) had 6–25 yr of health care experience, and 16.0% (n = 459) had <6 yr of experience. The respondents represented an array of health care settings; 27.0% (n = 774) were from inpatient facilities, 17.3% (n = 496) worked in outpatient facilities, 22.6% (n = 648) were from residential settings, and 13.5% (n = 387) worked in community-based organizations. The remainder of the respondents indicated that they worked in multiple levels of care or in a setting other than the presented options, or they did not respond to the question.

The questionnaire was distributed throughout the United States, and respondents represented every state, the District of Columbia, and Puerto Rico. Geographic locations were collapsed into five regions. A total of 29.7% of respondents were located in the Midwest (n = 850); 26%, in the Northeast (n = 741); 19.1%, in the Southeast (n = 548); 16.5%, in the West (n = 480); and 7.2%, in the South (n = 207; percentages do not add to 100% because 43 people did not respond to the question). Participation was comparable from urban (41%, n = 1,176) and suburban (40%, n = 1,148) locations. Only 545 respondents (19%) were in rural locations.

The bulk of the survey consisted of questions about 19 factors that may prevent development of a driving or community mobility program. Respondents identified the extent to which each factor was a barrier by choosing one of the following: has no impact on program development, small barrier, moderate barrier, significant barrier, this factor alone prevents program development, not sure of the impact, or not applicable to my facility.Table 1 shows the percentage of respondents who identified the barriers to program development as being a moderate or significant barrier or as alone preventing program development. At least half of respondents identified the following as barriers: private pay for services, funding to develop a program, trained specialists to provide services, third-party reimbursement to pay for services, concern about risk and liability, and clinician time to address issues. The barriers identified by fewer than 30% of the respondents were other professionals recognize need for services, physician support, and practitioner understanding of client needs.

Table 1.

Factors Identified as Moderate to Complete Barriers to Program Development

Program Barrier	% Respondents Who Identified Barrier
Private pay for services	57.3
Funding to develop a program	57.1
Trained specialists to provide services	55.0
Third-party reimbursement to pay for services	54.0
Concern about risk and liability	50.1
Clinician time to address issues	50.1
Transportation to and from services	48.4
Physical environment barriers	47.4
Willingness to seek and use services	45.2
Standard business operations	41.5
Infrastructure to support referral and use	40.1
Medical model focus	38.1
Administrative support	37.1
Standardization of assessment and intervention	35.8
Public awareness of older driver issues	35.0
Demand or request for services	31.9
Other professionals recognize need for services	29.6
Physician support	28.2
Practitioner understanding of client need	23.9

View Large

Table 1.

Factors Identified as Moderate to Complete Barriers to Program Development

Program Barrier	% Respondents Who Identified Barrier
Private pay for services	57.3
Funding to develop a program	57.1
Trained specialists to provide services	55.0
Third-party reimbursement to pay for services	54.0
Concern about risk and liability	50.1
Clinician time to address issues	50.1
Transportation to and from services	48.4
Physical environment barriers	47.4
Willingness to seek and use services	45.2
Standard business operations	41.5
Infrastructure to support referral and use	40.1
Medical model focus	38.1
Administrative support	37.1
Standardization of assessment and intervention	35.8
Public awareness of older driver issues	35.0
Demand or request for services	31.9
Other professionals recognize need for services	29.6
Physician support	28.2
Practitioner understanding of client need	23.9

We also examined whether identified barriers were real or perceived by gathering information on respondents’ prior program development experience. In a comparison of barriers identified by respondents with and without program development experience, we found no statistically significant differences and concluded that there was no difference between the real and perceived barriers acknowledged by the occupational therapists, managers, and administrators.

A correlation analysis conducted to identify relationships among the 19 barriers showed a moderate to good relationship among all barriers. Results of the relationships ranged from r_s = .503 to .810. Three of the correlations had good to excellent relationships: third-party reimbursement to pay for services and funding to develop a program (r_s = .752), infrastructure to support referrals and use and other professionals recognize need for services (r_s = .756), and third-party reimbursement to pay for services and private pay for services (r_s = .810).

Finally, we investigated the relationships between the 19 identified barriers and several respondent and setting characteristics, including practitioner level (occupational therapist, manager, and administrator), facility type (inpatient, outpatient, residential, and community), population density (urban, suburban, and rural), decision-making power (maximum, moderate, and minimal control over program development), and program development experience (experience and no experience). We found no significant relationships between any of the barriers and the respondent characteristics and settings. Because no significant differences in perceptions were identified among respondents from different regions of the country, levels of practitioner, facility type, professional experience, and decision-making control, we surmised that experiences with barriers were similar across the different characteristics. We therefore did no further analysis with stratifications by those characteristics.

In addition to experiencing barriers in developing programs, practitioners also experience barriers when addressing driving in practice with their clients. Some of the barriers are similar to those encountered in developing programs, but others are clearly unique to clients and their human fears and responses. To examine the prevalence of client barriers, we removed from the analysis sample those who did not respond, did not work directly with clients, or had not worked with clients with driving and community mobility concerns. The resultant sample of 2,404 participants identified at least one barrier when working with clients on issues related to driving and community mobility (Table 2). At least 60% of the respondents identified the barriers of client fear of losing driver’s license, client or family lack of insight about deficits, lack of alternative transportation options, and client or family reluctance to adhere to recommendations. The least identified client barriers (<0.5%) were lack of physician support, insufficient infrastructure in health care, and lack of therapists.

Table 2.

Client Barriers Respondents Reported Encountering in Driving and Community Mobility Programs

Client Barrier	% Respondents Reporting
Fear of losing driver’s license	84.9
Lack of insight about deficits	83.9
Lack of alternative transportation options	63.9
Reluctance to adhere to recommendations	62.2
Shortage of programs	59.8
Lack of assessment tools	49.3
Cost of services	48.8
Lack of reimbursement	46.2

View Large

Table 2.

Client Barriers Respondents Reported Encountering in Driving and Community Mobility Programs

Client Barrier	% Respondents Reporting
Fear of losing driver’s license	84.9
Lack of insight about deficits	83.9
Lack of alternative transportation options	63.9
Reluctance to adhere to recommendations	62.2
Shortage of programs	59.8
Lack of assessment tools	49.3
Cost of services	48.8
Lack of reimbursement	46.2

Discussion

We explored the experienced and perceived barriers that health care administrators, managers, and therapists encountered when developing and sustaining driving and community mobility programs. The respondents were substantially experienced in their health care careers and represented an array of health care settings, geographic locales, and population densities. In addition, many respondents had experience in developing programs, a background that validates their responses as reflecting an understanding of the program development process and familiarity with barriers that exist in their field. Because of the broad representation of the sample, we believe that the results from this study are representative of the state of affairs in driving and community mobility program development throughout the United States.

In a review of the literature across regions of the country, disciplines, and practice areas, we found 19 barriers that were commonly encountered in the health or community program development process. Those barriers involved both personal factors (i.e., associated with individual training, experience, comfort) and contextual factors (i.e., associated with the physical, social, cultural, and institutional environments). Although at least some participants identified the existence of all 19 barriers, the barriers identified by ≥40% of the sample were largely contextual, suggesting that the health care or community systems themselves are preventing program development. These barriers included lack of fiscal support; insufficient infrastructure in staffing, operations, transportation, and referral networks; and institutional obstacles related to risk and demand for clinician productivity. It is noteworthy that three of the top four identified program development barriers were related to fiscal support of services (third-party reimbursement issues, funding to develop a program, and private pay by clients for services), indicating that barriers exist outside of the institution within the larger health care infrastructure. The predominance of contextual barriers over personal barriers should be considered when developing solutions so that resources can be appropriately allocated to target contextual changes rather than personal barriers.

It was important, from a remediation planning perspective, to determine whether certain barriers were more prevalent in certain areas of the country, in specific settings, or among one level of practitioner over another. The analyses run to identify differences in barriers experienced between practitioner levels, facility types, regions, decision-making control, and program development experience revealed no significant differences. We concluded that barriers are equally as discriminating across locations, facility types, levels of practitioner, decision-making control, and levels of experience in developing programs. Additionally, we examined the relationships between the barriers and found them to be highly correlated with each other, ranging in strength of relationship from good to excellent. We concluded that because all barriers are highly associated, when one barrier is eliminated or overcome, there may be a subsequent positive impact on the other barriers. The pervasiveness and strength of these barriers was initially discouraging because they indicated the massive scope of the remediation necessary. The highly associated and nondiscriminating nature of the barriers was also promising, however, because it indicated that a single resource toolkit would be sufficient to meet the program development and sustainment needs of all practitioners in all settings.

We gave participants the opportunity to respond to an open-ended question regarding barriers to developing and sustaining driving and community mobility programs. Many respondents reported the need for increased educational opportunities for practitioners, the public, and other medical professionals. Some stated that when medical doctors refer clients for driving rehabilitation, they often make the referral to another medical doctor, such as a neurologist, instead of an occupational therapist or a driving and community mobility specialist. The respondents ascribed these inappropriate referrals to the medical practitioners’ lack of knowledge about the scope of occupational therapy practice and about the skilled interventions provided by older driver and community mobility programs. In addition, some participants mentioned an interest in learning about assessment tools being used by other professionals or programs to help predict driving capability. Participants in various areas of the country, both rural and otherwise, mentioned lack of alternative transportation options as a barrier to program development. As other researchers have reported (Bauer et al., 2003; O’Neill et al., 2000), lack of alternate transportation is one reason older adults do not stop driving even when they know cessation is necessary.

After this study, AOTA sponsored a 2-day consensus conference attended by 19 experts, including representatives from the driving rehabilitation practice and community mobility area, the community mobility industry, and the traffic safety industry as well as occupational therapists with expertise in program development, risk management, education, and practice issues. During this conference, we presented the results of this study, after which a professional facilitator organized breakout and brainstorming sessions. The attendees ultimately agreed on seven distinct areas of focus for a resource toolkit: (1) Model Program, (2) Risk Identification and Management, (3) Capacity Building: The Delivery of Driving Services, (4) Evidence-Based Practice for Driving and Community Mobility, (5) Funding for Programs and Services, (6) Promoting Participation in Driver Programs, and (7) Strategic Alliances. Over the course of the next year, an online resource toolkit was built by Wendy Stav and the coordinator of AOTA’s Older Driver initiative and published on AOTA’s Web site (www.aota.org/Older-Driver/Professionals/Toolkit/Programs.aspx). The program development resource toolkit is an evolving source of information; additional documents are included as they are written or become available. For example, a recent addition is a program evaluation measuring the utility of the toolkit, which to date has revealed overwhelming satisfaction with the content, structure, and accessibility of the resource. Contributions from additional experts and agencies have been solicited by AOTA and have been executed through contracts and competitive grants.

Future Research

Further research is recommended to discover phenomena and details about the barriers to establishing driving rehabilitation and community mobility programs to ensure the most effective outcome of the resource toolkit. A qualitative study has been conducted by Wendy Stav to capture the experiences of people who have developed driving rehabilitation and community mobility programs. This firsthand perspective, scheduled for publication in a future issue of this journal, provided further insight into the barriers and information on how to overcome the obstacles experienced in program development. Beyond these practitioners’ perspectives, more research should be conducted to better understand the roles and barriers facing administrators and managers, given that they often possess the power and influence associated with program development and resource allocation. In addition, it would be beneficial to examine clients’ perspectives on the barriers they encounter in using driving and community mobility programs to examine how closely the client-identified barriers match the client barriers that health care practitioners identified (see Table 2).

An important area for follow-up study is the effectiveness of the resource toolkit in terms of how many programs have used the toolkit in the program development process, how many have remained operational, and whether the toolkit was beneficial to the process. Results from such studies could identify whether the toolkit is missing any important components. The toolkit may then be added to and improved on for further distribution. In addition, demonstrating that the resource toolkit is beneficial to facilities will validate continued funding for similar studies and resource toolkits by NHTSA and other transportation and driving services.

Limitations

This research study has some limitations. The study was made possible by funding through NHTSA and was administered by AOTA, which guided all aspects of the project. These organizations provided guidelines for developing and disseminating the data collection instrument that, although beneficial, may have limited our ability to independently design the study. For example, AOTA selected the reviewers of the data collection instrument and chose the external vendor that managed the Web-based questionnaire.

We attempted to recruit a representative sample of non-AOTA members, but this group was limited to 2.5% of the sample. Although the sample size was large, most respondents belonged to AOTA, potentially limiting the study because members of professional organizations may be inherently more involved and more concerned about professional issues than nonmembers. It would also have been beneficial to obtain a more interdisciplinary perspective so that the results are not considered biased.

During the cleaning of the data, some responses were reassigned to newly collapsed categories for ease in managing the data; doing so may have limited the elaboration of the responses. Additionally, compressing the data increases the chances of human error, which might have skewed some of the results.

In some of the open-ended questions, many respondents replied that the study was not applicable to their setting. We felt that those respondents may have self-limited their scope of practice. For example, only a few respondents in pediatric settings reported that they felt driving programs were necessary and needed to be addressed in their facility. Many young clients with cognitive or physical deficits, however, can benefit from participating in driving rehabilitation programs. In addition, pediatric clients who cannot benefit from driving rehabilitation programs may need community mobility programs that address child passenger safety, pedestrian safety, bicycle safety, transit use, and alternative means of mobility common in pediatric populations, such as skateboarding.

Conclusion

Our investigation into the shortage of driving rehabilitation and community mobility programs to meet the needs of the aging and general rehabilitation populations revealed a substantial number of barriers that are largely contextual. The barriers are consistent with program development barriers identified in the national and international literature and across disciplines. Stakeholders should be concerned, because not only are the barriers preventing new program development, but the number of programs is also declining yearly because organizations are not able to sustain operations in the presence of the barriers. The identified barriers are numerous, pervasive, and widespread and will require systemic change well beyond training practitioners in the nuances of the practice area. Advocacy efforts on both a micro and a macro level are necessary to institute systemwide changes, alter perceptions, modify policies, and build infrastructure to develop and sustain programs that will support engagement in driving and community mobility as a highly valued occupation.

Acknowledgments

We acknowledge the research contributions of Sanjita Bhandari and Karen Martz in partial completion of their master's degree in occupational therapy. We also acknowledge the administrative support of AOTA—specifically, Maureen Peterson, Laurel Radley, and Elin Schold Davis—in reviewing each phase of this project. We also thank NHTSA for financial support that allowed the execution of this study. This study was presented at a Consensus Conference convened at AOTA National Headquarters in September 2007; at the AOTA Annual Conference in Long Beach, California, in 2008; and at the Maryland Older Driver Research Consortium in 2008.

References

American Occupational Therapy Association. (2008). Occupational therapy practice framework: Domain and process (2nd ed.). American Journal of Occupational Therapy, 62, 625–683. [Article] [PubMed]

American Occupational Therapy Association. (2010a). Driving and community mobility. American Journal of Occupational Therapy, 64(Suppl.)S112–S124.

American Occupational Therapy Association. (2010b). Finding a driving specialist. Retrieved March 8, 2011, from www1.aota.org/driver_search/index.aspx

Bauer, M. J., Adler, G., Kuskowski, M. A., & Rottunda, S. (2003). The influence of age and gender on the driving patterns of older adults. Journal of Women and Aging, 15, 3–1610.1300/J074v15n04_02 [Article] [PubMed]

Carr, D. B. (2000). The older adult driver. American Family Physician, 61, 141–146, 148. [PubMed]

Carr, D. B., Duchek, J. M., Meuser, T. M., & Morris, J. C. (2006). Older adult drivers with cognitive impairment. American Family Physician, 73, 1029–1036. [PubMed]

Centers for Disease Control and Prevention. (2007). Older adult drivers: Fact sheet. Retrieved May 24, 2010, from www.cdc.gov/MotorVehicleSafety/Older_Adult_Drivers/adult-drivers_factsheet.html

Eberhard, J. (2008). Older drivers’ “high per-mile crash involvement”: The implications for licensing authorities. Traffic Injury Prevention, 9, 284–29010.1080/15389580801895236 [Article] [PubMed]

Gardezi, F., Wilson, K. G., Man-Son-Hing, M., Marshall, S. C., Molnar, F. J., Dobbs, B. M.et al (2006). Qualitative research on older drivers. Clinical Gerontologist, 30, 5–2210.1300/J018v30n01_02 [Article]

Granda, T. M., & Thompson, S. (2006). The older driver comes of age. Public Roads, 69, 26–33.

Marottoli, R. A., Mendes de Leon, C. F., Glass, T. A., Williams, C. S., Cooney, L. M., Jr., Berkman, L. F.et al (1997). Driving cessation and increased depressive symptoms: Prospective evidence from the New Haven EPESE. Journal of the American Geriatrics Society, 45, 202–206. [PubMed]

National Highway Traffic Safety Administration. (2009). Traffic safety facts 2008 data: Older population (Publication No. DOT-HS-811-161). Washington, DC: Author.

Odenheimer, G. L. (2006). Driver safety in older adults: The physician’s role in assessing driving skills of older patients. Geriatrics, 61, 14–21. [PubMed]

O’Neill, D., Bruce, I., Kirby, M., & Lawlor, B. (2000). Older drivers, driving practices and health issues. Clinical Gerontologist, 22, 47–5410.1300/J018v22n01_05 [Article]

Stav, W. B., Justiss, M. D., Belchior, P., & Lanford, D. (2006). Clinical practice in driving rehabilitation. Topics in Geriatric Rehabilitation, 22, 153–161. [Article]

U.S. Government Accountability Office. (2007). Older driver safety: Knowledge sharing should help states prepare for increase in older driver population (Publication No. GAO-07-413). Washington, DC: Author.

Table 1.

Factors Identified as Moderate to Complete Barriers to Program Development

Program Barrier	% Respondents Who Identified Barrier
Private pay for services	57.3
Funding to develop a program	57.1
Trained specialists to provide services	55.0
Third-party reimbursement to pay for services	54.0
Concern about risk and liability	50.1
Clinician time to address issues	50.1
Transportation to and from services	48.4
Physical environment barriers	47.4
Willingness to seek and use services	45.2
Standard business operations	41.5
Infrastructure to support referral and use	40.1
Medical model focus	38.1
Administrative support	37.1
Standardization of assessment and intervention	35.8
Public awareness of older driver issues	35.0
Demand or request for services	31.9
Other professionals recognize need for services	29.6
Physician support	28.2
Practitioner understanding of client need	23.9

View Large

Table 1.

Factors Identified as Moderate to Complete Barriers to Program Development

Program Barrier	% Respondents Who Identified Barrier
Private pay for services	57.3
Funding to develop a program	57.1
Trained specialists to provide services	55.0
Third-party reimbursement to pay for services	54.0
Concern about risk and liability	50.1
Clinician time to address issues	50.1
Transportation to and from services	48.4
Physical environment barriers	47.4
Willingness to seek and use services	45.2
Standard business operations	41.5
Infrastructure to support referral and use	40.1
Medical model focus	38.1
Administrative support	37.1
Standardization of assessment and intervention	35.8
Public awareness of older driver issues	35.0
Demand or request for services	31.9
Other professionals recognize need for services	29.6
Physician support	28.2
Practitioner understanding of client need	23.9

Table 2.

Client Barriers Respondents Reported Encountering in Driving and Community Mobility Programs

Client Barrier	% Respondents Reporting
Fear of losing driver’s license	84.9
Lack of insight about deficits	83.9
Lack of alternative transportation options	63.9
Reluctance to adhere to recommendations	62.2
Shortage of programs	59.8
Lack of assessment tools	49.3
Cost of services	48.8
Lack of reimbursement	46.2

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Table 2.

Client Barriers Respondents Reported Encountering in Driving and Community Mobility Programs

Client Barrier	% Respondents Reporting
Fear of losing driver’s license	84.9
Lack of insight about deficits	83.9
Lack of alternative transportation options	63.9
Reluctance to adhere to recommendations	62.2
Shortage of programs	59.8
Lack of assessment tools	49.3
Cost of services	48.8
Lack of reimbursement	46.2