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Determinants of nutrition appointment non-attendance among male veterans

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Title:
Determinants of nutrition appointment non-attendance among male veterans
Physical Description:
Book
Language:
English
Creator:
Bell, Claire Fontenot
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
Publication Date:

Subjects

Subjects / Keywords:
Veterans   ( mesh )
Nutrition   ( mesh )
Health Services   ( mesh )
Patient Compliance   ( mesh )
No-shows
Military
Non-attendance
Outpatient
Dietitian
Dissertations, Academic -- Community and Family Health -- Masters -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: During fiscal years 2006 and 2007, nearly 1 in 4 Veterans failed to keep their individual nutrition appointments, impeding clinic workflow, productivity, and management of weight and nutrition related health conditions. The purpose of this study was to identify determinants of nutrition appointment attendance in the Veteran population. This study examined the cognitive and structural factors that influence nutrition appointment attendance. Specifically, the study sought to determine: Veteran reported reasons for non-attendance and factors associated with appointment attendance. The research design entailed sequential use of qualitative and quantitative methods. Individual, semi-structured interviews and a mail survey were used to identify factors associated with outpatient nutrition appointment attendance.Seventeen individuals were purposively selected to represent appointment attenders (8 individuals) and non-attenders (9 individuals) in the following age groups: 18-44, 45-64, and 65 and older. Individual interviews were analyzed using constant comparative analysis. For the survey portion of the study, 349 surveys were collected. Descriptive statistics were used to summarize demographic characteristics of the survey sample. Bivariate comparisons of attenders and non-attenders revealed significant relationships between appointment keeping and the following variables: past nutrition appointment attendance, non-VA insurance, health status, income, BMI, forgetting, satisfaction, perceived importance, understanding of scheduling system, RD knowledge, family support, how referred, reminders, input to appointment time, travel, weather, difficulty with transportation, family care, feeling well, cost, parking time, and preferred day.Regression analyses suggest that only perceived family support, past attendance history, health status, and BMI remained correlated with appointment keeping when controlling for other factors. The results of this study will be used to identify ways to reduce no-shows thus increasing clinic efficiency of ambulatory care nutrition programs. The impact of increasing nutrition appointment attendance includes: improved access to nutrition appointments, more efficient use of resources, improved management of nutrition related conditions, and improved patient satisfaction.
Thesis:
Thesis (M.S.P.H.)--University of South Florida, 2009.
Bibliography:
Includes bibliographical references.
System Details:
Mode of access: World Wide Web.
System Details:
System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Claire Fontenot Bell.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 129 pages.

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aleph - 002063804
oclc - 557456863
usfldc doi - E14-SFE0003234
usfldc handle - e14.3234
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ABSTRACT: During fiscal years 2006 and 2007, nearly 1 in 4 Veterans failed to keep their individual nutrition appointments, impeding clinic workflow, productivity, and management of weight and nutrition related health conditions. The purpose of this study was to identify determinants of nutrition appointment attendance in the Veteran population. This study examined the cognitive and structural factors that influence nutrition appointment attendance. Specifically, the study sought to determine: Veteran reported reasons for non-attendance and factors associated with appointment attendance. The research design entailed sequential use of qualitative and quantitative methods. Individual, semi-structured interviews and a mail survey were used to identify factors associated with outpatient nutrition appointment attendance.Seventeen individuals were purposively selected to represent appointment attenders (8 individuals) and non-attenders (9 individuals) in the following age groups: 18-44, 45-64, and 65 and older. Individual interviews were analyzed using constant comparative analysis. For the survey portion of the study, 349 surveys were collected. Descriptive statistics were used to summarize demographic characteristics of the survey sample. Bivariate comparisons of attenders and non-attenders revealed significant relationships between appointment keeping and the following variables: past nutrition appointment attendance, non-VA insurance, health status, income, BMI, forgetting, satisfaction, perceived importance, understanding of scheduling system, RD knowledge, family support, how referred, reminders, input to appointment time, travel, weather, difficulty with transportation, family care, feeling well, cost, parking time, and preferred day.Regression analyses suggest that only perceived family support, past attendance history, health status, and BMI remained correlated with appointment keeping when controlling for other factors. The results of this study will be used to identify ways to reduce no-shows thus increasing clinic efficiency of ambulatory care nutrition programs. The impact of increasing nutrition appointment attendance includes: improved access to nutrition appointments, more efficient use of resources, improved management of nutrition related conditions, and improved patient satisfaction.
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Determinants of Nutrition Appointment Non-Attendance among Male Veterans by Claire Fontenot Bell A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Public Health Department of Community and Family Health College of Public Health University of South Florida Major Professor: Ca rol Bryant, Ph.D. Committee Members: Kay Perrin, Ph.D. Rita Debate, Ph.D. John Ferron, Ph.D. Date of Approval: November 6, 2009 Keywords: no-shows, military, non-attendance, outpatient, dietitian Copyright 2009, Claire Fontenot Bell

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Dedication This research is dedicated to our nati ons Veterans. To the World War II Veteran, who at 81 wanted to work on weight manage ment, despite having starved as a POW sixty years before. To the 40 something OEF/OIF Veteran who worked full time, went to school full time, and still found the time to attend nutrition appointments, make time for exercise and eating right and im prove his health. To the 76 year old who lost 16 lbs and prevented diabetes. To the 60 something Vietnam Veteran, who struggles with poor sleep and night eating, and atte nded nutrition appointments for weight management. This is a glimpse at the people who have touched my work and inspired my research endeavors. But there are a grea ter number of people this thes is is also dedicated to, the Veterans who did not attend nutrition appoint ments, who dietitians do not have the chance to help. You are among the many indi viduals who inspired me to do complete this research.

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Acknowledgments I would like to thank the Department of Nutrition and Food Service of the James A. Haley Veterans Hospital for supporting this endeavor. Many faculty members have also been invaluable, but I would like to es pecially thank Carol Bryant who advised me through this process. Finally, Id like to thank my family, friends, and co-workers who listened, counseled, and cheered me on as I prop osed, researched, and wrote this thesis. Your shoulders held me up and pushed me along when I needed it, and I thank you! With the support of many, I was able to lear n that character consists of what you do on the third and fourth tries (James A. Michener).

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i Table of Contents LIST OF TABLES ............................................................................................................. iv LIST OF FIGURES ............................................................................................................ vABSTRACT ...................................................................................................................... viCHAPTER 1 STATEMENT OF THE PROBLEM ............................................................ 1Introduction ............................................................................................................. 1Statement of the Problem ........................................................................................ 2Need for Study ........................................................................................................ 6Research Questions ................................................................................................. 6CHAPTER 2 LITERATURE REVIEW ............................................................................. 7Introduction ............................................................................................................. 7Veterans Administration Health Care System ........................................................ 7Appointment Non-Attendance .............................................................................. 11Demographic Correlates ....................................................................................... 15Socioeconomic Status and Education Level ............................................. 17Employment Status ................................................................................... 18Insurance ................................................................................................... 19Age ............................................................................................................ 20Gender ....................................................................................................... 21Race........................................................................................................... 21Family Size and Composition ................................................................... 22History of Mental Illness .......................................................................... 23Determinants of Non-Attendance ......................................................................... 24Cognitive Factors .................................................................................................. 24Forgetting .................................................................................................. 24Perceived Importance ................................................................................ 24Perceived Severity .................................................................................... 25Lack of Understanding .............................................................................. 25Social Factors ........................................................................................................ 26Respect ...................................................................................................... 26Social Support ........................................................................................... 27Provider Recommendation and Support ................................................... 28Emotional Factors ................................................................................................. 29Fear and Anxiety ....................................................................................... 29Structural and Logi stical Factors .......................................................................... 30Wait Times ................................................................................................ 31Difficulty with Scheduling System ........................................................... 31

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ii Competing Priorities ................................................................................. 32Other ......................................................................................................... 34Nutrition Specific .................................................................................................. 34Conclusion ............................................................................................................ 36CHAPTER 3 METHODS ................................................................................................. 38Introduction ........................................................................................................... 38Purpose & Research Questions ............................................................................. 38Study design .......................................................................................................... 39Population and Sample ......................................................................................... 39Sample Selection ................................................................................................... 40Sample Size ........................................................................................................... 40Interview Sample ...................................................................................... 40Survey Sample .......................................................................................... 42Data Collection ..................................................................................................... 43Interviews .................................................................................................. 43Surveys ...................................................................................................... 43Instrumentation ..................................................................................................... 45Data Management ................................................................................................. 48Data Analysis ........................................................................................................ 48Interviews .................................................................................................. 48Surveys ...................................................................................................... 49Hypotheses ............................................................................................................ 50CHAPTER 4 RESULTS ................................................................................................... 51Introduction ........................................................................................................... 51Interview Sample .................................................................................................. 51Reasons for Missing Appointments ...................................................................... 52Structural ............................................................................................................... 52Competing Demands ................................................................................. 52Transportation difficulty ........................................................................... 53Scheduling Difficulty ................................................................................ 55Feeling Unwell ...................................................................................................... 57Cognitive ............................................................................................................... 57Forgetting .................................................................................................. 57Experience with Past Appointment ........................................................... 58Knowledge Not New or Useful ................................................................. 58Attitude Toward VA ................................................................................. 60Social..................................................................................................................... 61Family Support.......................................................................................... 61Provider support ........................................................................................ 62Survey Results ...................................................................................................... 65Demographic and Other B ackground Characteristics ........................................... 71Prior Nutrition Appointment Attendance .................................................. 71Health Status ............................................................................................. 71Social..................................................................................................................... 74

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iii Structural ............................................................................................................... 75Hypothesis Testing................................................................................................ 77CHAPTER 5 DISCUSSI ON & CONCLUSION .............................................................. 83Introduction ........................................................................................................... 83Research Summary ............................................................................................... 83Research Summary ............................................................................................... 84Discussion of Results ............................................................................................ 85Social......................................................................................................... 86Structural ................................................................................................... 87Study Strengths ..................................................................................................... 88Limitations ............................................................................................................ 88Methodological Difficulties ...................................................................... 88Bias ........................................................................................................... 89Chance....................................................................................................... 90External Validity ....................................................................................... 90Recommendations for Future Research ................................................................ 90Implications........................................................................................................... 91REFERENCES ................................................................................................................. 94APPENDICES ................................................................................................................ 102Appendix A, Historical Appointment Trends ..................................................... 103Appendix B, Pre-letter (Phone Interview) .......................................................... 104Appendix C, Telephone Recruitment and Interview Script ................................ 106Appendix D, Survey Variables ........................................................................... 110Appendix E, Survey Cover Letter ....................................................................... 112Appendix F, Survey Reminder Post Card ........................................................... 114Appendix G, Third Mailing Cover Letter ........................................................... 115Appendix H, Survey............................................................................................ 117Appendix I, Summar y of Missingness ................................................................ 123Appendix J, Demographic Vari ables Descriptive Summary .............................. 126

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iv LIST OF TABLES Table 1 Obesity Prevalence in Veterans vs. General Population ..............................2 Table 2 Diabetes Prevalence in Veterans vs. Non-Veterans .....................................3 Table 3 Reduced Utilization of Se rvices Associated With MNT .............................4 Table 4 Appointment Attendance FY2006 & 2007 ................................................11 Table 5 Correlates of Appointment Attendance .....................................................16 Table 6 Interview Sampling Matrix ........................................................................41 Table 7 Actual Interview Sample............................................................................42 Table 8 Historical Attendance Data, 2007 ..............................................................42 Table 9 Survey Changes .........................................................................................47 Table 10 Survey Response Rate................................................................................64 Table 11 Significant Survey Results .........................................................................66 Table 12 Non-Significant Survey Results .................................................................69 Table 13 Significance of Control Variables in Regression Models ..........................78 Table 14 Logistic Regression Results .......................................................................79

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v LIST OF FIGURES Figure 1 Referring Diagnosis to Ambulatory Care Nutrition Clinics ......................10 Figure 2 Appointment trends FY2007....................................................................103 Figure 3 Appointment trends FY2006....................................................................103

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vi Determinants of Nutrition Appointment Non-Attendance among Male Veterans Claire Fontenot Bell ABSTRACT During fiscal years 2006 and 2007, nearly 1 in 4 Veterans failed to keep their individual nutrition appointm ents, imp eding clinic workflow, productivity, and management of weight and nutrition related health conditions. The purpose of this study was to identify determinants of nutrition appointment attendance in the Veteran population. This study examined the cognitive and structural fact ors that influence nutrition appointment attendance. Specificall y, the study sought to determine: Veteran reported reasons for non-attendance and factors associated with appointment attendance. The research design entailed sequential use of qualitative and quantitative methods. Individual, semi-structured interviews and a mail survey were used to identify factors associated with outpatient nutrition appointment attendance. Sevent een individuals were purposively selected to represent appointmen t attenders (8 indivi duals) and non-attenders (9 individuals) in the following age groups: 1844, 45-64, and 65 and older. Individual interviews were analyzed using constant comp arative analysis. For the survey portion of the study, 349 surveys were collected. Descri ptive statistics were used to summarize demographic characteristics of the survey sample. Bivariate comparisons of attenders and non-attenders revealed significant relati onships between appointment keeping and the following variables: past nutrition appoi ntment attendance, non-VA insurance, health status, income, BMI, forget ting, satisfaction, pe rceived importance, understanding of

PAGE 10

vii scheduling system, RD knowledge, family s upport, how referred, reminders, input to appointment time, travel, weather, difficulty with transportation, family care, feeling well, cost, parking time, and preferred da y. Regression analyses suggest that only perceived family support, past attendance history, health status, and BMI remained correlated with appointment k eeping when controlling for othe r factors. The results of this study will be used to identify ways to reduce no-shows thus increasing clinic efficiency of ambulatory care nutrition programs. The impact of increasing nutrition appointment attendance includes: improved access to nutrition appointments, more efficient use of resources, improved manage ment of nutrition related conditions, and improved patient satisfaction

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1 CHAPTER 1 STATEMENT OF THE PROBLEM Introduction The Veterans Adm inistration ( VA) is the largest integrated single payer system in the United States, providing medical care to over 5.5 million Veterans nationwide (Department of Veterans Affairs, 2007). Th e busiest VA healthcare facility in the nation, the James A. Haley Veterans Hospital (JAHVAH), provides approximately 1.5 million individual outpatient visits each year. Nutrition services are an important co mponent of the JAHVAH ambulatory care system, with three full time registered dietitians providing approximately 3000 nutrition counseling sessions each year. Despite this accomplishment, the efficiency of the JAHVAH nutrition services could be improved if the proportion of patients who fail to keep their nutrition appointments is reduced. During fiscal years 2006 and 2007, almost one in four Veterans failed to keep th eir nutrition appointme nts, impeding clinic workflow and productivity. This study is designed to identify the f actors that influence nutrition appointment attendance and provide insights needed to reduce the no-show rate. The rest of this chapter will discuss the need and purpose of the study. Ch apter Two will review the literature on non-attendance of medical appointments. Chapter Three will present an overview of the proposed design and methods of the study. Chapter Four will present results and Chapter Five will provide discussion and conclusions.

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2 Statement of the Problem JAHVAH pr ovides nutrition counseling to patients referred from seven primary care or ambulatory clinics and specialty c linics. The most common medical problems referred for nutrition counseling are overw eight and obesity related disordershyperlipidemia, hypertension, and diabetes. As seen in Tables 1 and 2, obesity and diabetes prevalence among Veterans is sli ghtly higher than the national average. Diabetes, vascular diseases, and other co -morbid conditions are also higher among VA users than the general popul ation (Agha, Lofgren, VanRuiswek, & Layde, 2000; Nowicki et al., 2003; Reiber, Koepsell, Maynard, Haas, & Boyko, 2004). Table 1 Obesity Prevalence in Veterans vs. General Population Veterans National Average 2003-04 Men Women Men Women Overweight 73% 68.4% 70.8% 61.8% Obese 32.9% 37.4% 31.1% 33.2% Note. Adapted from Obesity Prevalence Among Veterans at Veterans Affairs Medical Facilities by S.R. Das, L.S. Kinsinger, W.S. Yancy, A. Wang, W. Ciesco, M. Burdick, and S.J. Yevich, 2005, American Journal of Preventative Medicine, 28 (3), p.292 and Prevalence of Overweight and Obesity in the United States, 1999-2004 by C.L. Ogden, M.D. Carroll, L.R. Curtin, M.A. McDowell, C.J. Tabak, and K.M. Flegal, 2006, Journal of the American Medical Association, 295(13), p.1551.

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3 Table 2 Diabetes Prevalence in Veterans vs. Non-Veterans All male Veterans Male Veterans using VA services General Population Diabetes prevalence 12% 16% 7.9% Note. From Prevalence of Obesity, Diabetes, and Obes ity Related Health Risk Factors by A.I. Mokdad, E.S. Ford, B.A. Bowman, 2003, Journal of the American Medical Association, 289, p. 77 and from Diabetes in NonVeterans, Veterans, and Veterans recei ving Department of Veterans Affairs Health Care by G.E. Reiber, T.D. Koepsell, C. Maynard, L.B. Haas, E.J. Boyko, 2004 Diabetes Care, 27, Suppl 2: p.B5. The health and financial implications of obesity and its co -morbidities are wellknown (USDHHS, 2001). Poor nutrition is correl ated with several of the leading causes of death including: heart disease, stroke, cancer, diabetes, and chronic obstructive pulmonary disease (Pavlovich, Waters, Weller, & Bass, 2004). The direct and indirect consequences of overweight and obesity accounted for 9.1 percent of medical expenses in 1998 and may have reached as high 92.6 b illion (in 2002 dollars ) (Finkelstein, Fiebelkorn, & Wang, 2003). Diabetes co sts totaled $132 billion in 2002 (American Diabetes Association) while the cost of car diovascular disease and stroke was estimated to be $403.1 billion in 2006 (American Heart Association, 2007). Medical nutrition therapy (MNT) provided by registered di etitians plays an important role in cost-savings and improved outcomes in diseases such as malnutrition, cancer, cardiovascular disease, and obesity (American Dietetic Association, 1995). Treatment of other nutrition-related medical problems referred for nutrition counseling

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4 gastrointestinal disorders, swallowing difficulty, and weight loss resulting from HIV, cancer, and other diseases also have im portant financial imp lications for the VA. For example, in HIV positive patients, nutriti on intervention can assist with weight maintenance, improve nutritional status, and may support enhanced outcomes (McKinley, Goodman-Block, Le sser, & Salbe, 1994). As outlined in Table 3, MNT is associated with the reduced utilization of hospital and phys ician services (Sheils, Rubin, & Stapleton, 1999). Adequate nutrition is e ssential to the treatment of both acute and chronic diseases (American Dietetic Association, 1995). Table 3 Reduced Utilization of Serv ices Associated with MNT Reduction in Hospital Services Reduction in Physician Services Patients with diabetes 9.5% 23.5% Patients with cardiovascular disease 8.6% 16.9% Note. From The Estimated Costs and Savings of Medical Nutrition Therapy: the Medicare Population. by J.F. Sheils, R. Rubin, D.C. Stapleton, 1999, Journal of the American Dietetic Association 99(4), p. 434. Regular attendance of nutriti on and lifestyle re lated programs is associated with improved outcomes. Among Veterans, studies have shown that those who attended cardiac rehabilitation programs regularly expe rienced greater improvements in exercise capacity than those who did not attend regul arly (Hershberger, Robertson, & Markert, 1999). Among non-Veterans participating in di abetes clinics, patie nts who attend 6 to 7 appointments had better blood gl ucose control as measured by A1c than those who did not show up (Rhee et al., 2003). Conversel y, Rohland (2004) reported that diabetes

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5 control was poorer in patients who missed appo intments compared to those who attended regularly. These findings sugge st that JAHVAHs nutrition service has not been able to realize its full potential to ma nage costly dietary problems be cause of high rates of nonattendance at outpatient appointments. Studies of outpatient appointment non-atte ndance also have shown that no-shows impede clinic workflow (Lacy, Paulman, Reuter, & Lovejoy, 2004) and may increase appointment waiting times (Hardy, O'Brien, & Furlong, 2001; Martin, Perfect, & Mantle, 2005). Increased waiting times most often refers to dela ys in scheduling, such as increased number of days between when the appointment is made and when the appointment occurs. Increased waiting times may also refer to the length of time a patient sits in the waiting area of a doctor's office. Short-notice cancellations of medical or educator appointments are expensive b ecause they cannot be easily filled, causing income loss without matching reduction in labor and facilities costs (Weigner, McMurrich, Yi, Lin, & Rodriquez, 2005). According to Sharp and Hamilton (2001), reducing non-attendance reduc es waiting times, which furt her reduces non-attendance, creating a virtuous cycle (p. 1082). Finally, frequent non-attendance may foster negative provider attitudes towards patients, which weakens providerpatient rapport. As Weigner et al. (2005) report: Failure to attend scheduled medical appointments increases the cost of medical care and may impact succes sful diabetes management.Short notice cancellations also impact the quali ty of overall patient care. Such cancellations reduce the number of appoi ntments available to all patients, thus some patients needing more prom pt medical attenti on may be placed

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6 on a waitlist. Furthermore, less freque nt attendance at a diabetes clinic has been associated with poore r glycemic control (p. 1791). Need for Study To im prove dietary management practices and the overall effici ency of nutrition services at the JAHVAH, it is important to understand the factors that affect nutrition appointment attendance. Whereas scholars have identified a variety of demographic correlates and other factors a ssociated with outpatient appoi ntment attendance, limited studies could be located that examined reasons patients fa il to attend nutrition counseling appointments. Research Questions This study will exam ine the cognitive a nd structural factors that influence appointment attendance. Individual, in-depth interviews and a mail survey will be used to identify factors that influence Veterans nutrition appointment attendance. Specific objectives are to determine: Research Question 1: What reasons do Veterans report for non-attendance for individual nutrition appointments? Research Question 2: Which factors are correlated w ith appointment nonattendance? Results of this study will be used to identify strategies for reducing the no-show rate for nutrition appointments and impr ove the ability of the JAHVAH to provide nutrition services to Veterans.

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7 CHAPTER 2 LITERATURE REVIEW Introduction The Departm ent of Veterans Affairs ( VA) operates national programs for health care, financial assistance, and burial benefits. Veterans He alth Administration (VHA) is the largest integrated single payer health care system in the United States, providing health care to a population that suffers fr om poorer health and lower socio-economic status compared to those who rely on priv ate sector insurance. Those who utilize VA healthcare services tend to be older, poorer, less educated and have significantly worse health status than private sector outpatient s. Prevalence of mental health problems and physical disability is higher in the Veteran population than th e general public (Nowicki et al., 2003). This literature review will focus on an important aspect of providing health care appointment attendance. There is a bundant literature on non-attendance, missed appointments, and no-shows in a variety of settings. However, literature on no-shows for nutrition appointments is limited. The fo llowing chapter will desc ribe the Veterans Administrative Health Care System and th e nutrition services offered by the JAHVAH in Tampa, Florida, and discuss the impact of no-shows on the provision of healthcare, demographic correlates, and de terminants of non-attendance. Veterans Administration Health Care System The Veterans Adm inistration is the sec ond largest of the 15 Cabinet departments and operates nationwide programs for health care, financial as sistance, and burial benefits for Veterans (Department of Vetera ns Affairs, 2007, p. 1). Healthcare is likely

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8 the most recognized benefit of the VA with more than 1400 sites of care including 155 medical centers, 872 ambulatory care and co mmunity based clinics, 135 nursing homes, 45 residential rehabilitation programs, 209 Veterans Centers, and 108 comprehensive home-care programs. Through these centers, the VA is able to provide an extensive range of medical, surgical, and rehabilitative care. Nearly 5.5 million people received care in 2006 with more than 60 million outpati ent visits. VAs fiscal year 2007 spending was projected to be $34.9 billi on for health care (Department of Veterans Affairs, 2007). As defined by eligibility criteria of th e VA, a Veteran is defined as anybody who has had active military service in the Arm y, Navy, Air Force, Marines, or Coast Guard (or Merchant Marines during WWII), and discharged under other than dishonorable conditions (Department of Veterans Affairs, 200 8). It should be not ed that Reservists and National Guard members that were called to active duty for combat operations have special eligibility and that VA health care is not limited to those who served in combat or have service-connected injuries or health c onditions (Department of Veterans Affairs, 2008). VA medical centers are likely the most prominent sources of healthcare provision within the VA system. The JAHVAH is a VA me dical center located in Tampa, Florida, with services that include: primary care, specialty clinics, testing, inpatient services including hospital admissions and surgery, outpatient ed ucation, physical therapy, occupational rehabilitation, vision care, a nd long term care facilities. Within close proximity to the main campus, the JAHVAH also provides mental health service, substance abuse recovery programs, and social rehabilitation programs. In addition to the

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9 main campus, there are also Community Based Outpatient Clinics (CBOC), which have been established to provide pr imary care in outlying areas. Nutrition services fit into this vast fram ework within the primary care setting, also known as ambulatory care. At the JAHVAH, ambulatory care clinics are arranged in teams of 4-10 providers (doctors, physician as sistants, or nurse practitioners), 4-6 nurses, a pharmacist, a social worker, and scheduling staff. Ambulatory care teams are assigned names such as Alpha, Bravo, Charlie, Delta, and Foxtrot. Three fulltime registered dietitians are assigned to primary care outpa tient nutrition. These three staff receive referrals from a total of seven outpatient clinics. Over 3000 outpatient nutrition appoi ntments are conducted annually in JAHVAHs ambulatory care clinics. A ch art review conducted by ambulatory care JAHVAH dietitians in 2006 revealed the majori ty of patients were referred for weight management and related conditions including diabetes or impaired fasting glucose, hyperlipidemia, and hypertension. See Figure 1 for a more detailed description of reasons for referral. The literature confir ms the prevalence of obesity and related conditions in the Veteran population which is re flected in reasons for referral. Seventythree percent of male Veterans are overwei ght while 33% are obese (Das et al., 2005) and 16% of the Veteran population has diabetes (Rieber et al., 2004). In comparison to normal weight Veterans, obese Veterans mo re often suffer from hypertension, diabetes, arthritis, chronic heartburn, kidney disease, a nd post-traumatic stress disorder (Arterburn, McDonell, Hedrick, Diehr, & Fihn, 2004). In another study of the Veteran population, Nowicki et al., (2003) found the proportion of co-morbidities such as diabetes, heart disease, hypertension, and jo int problems was lowest in normal weight patients and

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10 highest in overweight patients. It is evid ent that although patients are referred to nutrition for reasons beyond weight management, the majo rity of patients are seen for conditions related to overweight and obesity. Patients also attend nutrit ion appointments for concer ns including: underweight status related to HIV, cancer treatment or aging; as well as assistance with management of gastrointestinal conditions such as Celia cs disease, diverticulosis, gastroesophageal reflux disease (GERD); and alte red digestive function after ga strointestinal surgeries. These referrals are reflected in the 4% of ambulatory care nutrition appointments that were grouped into the other category of the 2006 chart review It is notable that the majority of patients with head and neck cance r, which often require aggressive nutrition intervention, are followed by a non-ambulatory care oncology dietitian, who manages the home tube feeding program. Figure 1 Referring Diagnosis to Ambulatory Care Nutrition Clinics Wt Reduction 44% DM/Hyperglycemia 27% Hyperlipidemia 17% Other 4% Hypertension 8%

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11 Appointment Non-Attendance Non-attendance to nutrition appointm ents is costly, not only to the health of patients, but also to the efficiency of the di etitian, ambulatory care c linics, and the VA. A review of appointment data for fiscal years 2006 and 2007 (FY2006 and FY2007) reveals ambulatory care nutrition is subject to these inefficiencies. For the purposes of this discussion, no-shows, missed appointments and non-attendance re fer to patients who miss appointments without calli ng to cancel or reschedule. Cancellations describe patients who call in advance or on the da y of the appointment to cancel and/or reschedule. A review of appointment da ta for FY2006 and FY2007 is summarized in Table 4. Table 4 Appointment attendance FY2006 and 2007 Fiscal Year No-shows Cancellations Total Seen 2006 768 2754 3115 2007 748 1600 2953 Note. Increased number of cancellations in 2006 was related to a restructuring and reorganization of the appointment systems. Cancellations include patient and administrative cancellations. Fiscal Year 2006: October 1, 2005 until September 30, 2006; Fiscal Year 2007: October 1, 2006 until September 30, 2007. Table information includes all scheduled patients for the above time period. The information included in Table 4 i ndicates no-show rate s of 24.7% and 25.3% in fiscal years 2006 and 2007 respectively. A month-by-month summary of this data can be found in Figures 2 and 3 in the appendix. Monthly data reveals an annual peak in appointment attendance in the spring months and an annual spike in missed appointments during the summer, particularly July and August. By looking at annual trends, it is

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12 apparent that some factors of attendance are unique to the JAHVAH Veteran population; within the population of thos e using JAHVAH, there is a la rge proportion of transient patients who spend the summer months outside of Florida. High rates of no-shows and cancellati ons prevent JAHVAH ambulatory care nutrition from realizing its fu ll potential to manage cost ly nutrition related health conditions. When appointments are missed, valu able opportunities for education are lost. This is unfortunate given that lifestyle inte rvention is an important aspect of disease management. Studies of cardiac rehabilitation and diabetes clinic patients have shown a correlation between increased appointment a ttendance and improved disease management (Hershberger et al., 1999; Rhee et al., 2003). The association of attrition from diabetes related appointments and adverse clinical ou tcomes is consistent across the literature (Gucciardi, DeMelo, Offenheim, Grace, & Stewart, 2007). Specifically, nutrition intervention is associated with decreased co sts and improved diseas e outcomes. Medical Nutrition Therapy (MNT) is associated with the reduced utiliza tion of hospital and physician services. In those with diabetes, MNT is associated w ith a 9.5% reduction in use of hospital services and a 23.5% reduction in use of physician services. In those with cardiovascular disease, MNT is associated with an 8.6% re duction in use of hospital services and a 16.9% reduction in use of phys ician services (Sheils et al., 1999). In addition to cost savings, regular a ppointment attendance and involvement in health care decisions is also associated with improved management of many chronic diseases. An open provider-patient relati onship is particularly important in the management of chronic conditions, such as diabetes, hypertensi on, coronary artery disease, and congestive heart failure (Beck, Daughtridge, & Sloane, 2002). When

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13 patients are informed and invol ved in decision making, they ar e more adherent to medical recommendations and carry out more health-r elated behavior change (e.g., exercise, smoking cessation, and dietary modification) (Beck et al., 2002, p. 25). Unfortunately, frequent non-attendance may fo ster negative provider attit udes towards patients, which weakens provider-patient rapport, and may ultimately impede the development of provider-patient rapport (Hussain-Gambles Neal, Dempsey, Lawlor, & Hodgson, 2004). As summarized by the American Dietetic Association (2001), the negative impact of failed appointments has been well documented: Low kept appointment rates contribute to under-treatment of clients, reduced potential to improve health/clini cal outcomes by inhibiting further individualization of therapy, loss of reinfo rcement to maintain health behaviors, and adversely affected continuity of care. In addition, low ke pt-appointment rates result in a disruption of client/care-prof essional relationship and decreased or lost opportunities for other clients to obtain a ppointments in a timely manner. Finally, missed appointments cause clinic inefficiency due to preparations for clients that do not arrive, disrupts work in clinics, and they lead to inefficient clinic scheduling processes, decreases in educational opportunities for teaching practices, lost revenu e, and indirectly increases in the cost of healthcare (p.935). Other studies of outpatient appointment at tendance elaborate on this point. The negative impact of no-show on clinic workflow was noted by Lacy, Paulman, Reuter, and Lovejoy (2004). A prominent negative imp act of no-shows is increased waiting times (Hardy, O'Brien, & Furlong, 2001; Martin, Perf ect, & Mantle, 2005). These increased wait times refer not only to time spent sitting in the lobby, but also to the number of days

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14 it may take to find an available appointment slot. No-shows increase waiting times because they occupy appointment bookings; when an individual no-shows that slot goes unused, creating longer wait times. Failed appointments are also associated with financial costs related to misused time, diffi cultly filling appointment slots, and income loss without matching reduction in labor and facilities costs (Martin et al, 2004; Weinger, McMurrich, Yi, Lin, & Rodriquez, 2005) Reducing missed appointments would contribute to reduced waiting times and more efficient use of resources (Hardy et al, 2001). The impact of reduced waiting times is illustrated by Sharp and Hamilton (2001), reducing non-attendance reduc es waiting times, which furt her reduces non-attendance, creating a virtuous cycle (p. 1082). The importance of appointment attendance to nutrition related appointments is described by Weinger et al (2005): Failure to attend scheduled medical appoi ntments increases the cost of medical care and may impact successful diabetes management. Short notice cancellations also impact th e quality of overall patient care. Such cancellations reduce the number of appointments available to all patients, thus some patients needing more prompt medical attention ma y be placed on a waitlist. Furthermore, less frequent attendance at a diabetes clinic has been associated with poorer glycemic control (p. 1791). Across the healthcare literature, studies have examined: patient characteristics associated with missed appointments, co mmon reasons for missed appointments, and interventions to improve appointment attenda nce. Factors that influence appointment attendance will be discussed in this chapter; a discussion of suggested interventions will

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15 be addressed in later chapters. More specifi cally, this chapter will review non-attendance in a variety of settings, incl uding primary care and specialty areas, such as internal medicine, genetics clinics, and oral facial su rgery. Some studies also looked at missed appointments in diabetes care, diabetes self-management, and cardiac rehabilitation programs. Studies examining factors that influence nutrition appoi ntment attendance will be addressed separately at the end of the chapter. Demographic Correlates Much of the literature regarding appointm ent non-attendance focuses on demographic correlates, as summarized in table 5.

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16 Table 5 Correlates of Appointment Attendance Correlate References Social-economic status Cooper, Weinman, & Horne, 2002; George & Rubin, 2003; Neal et al., 2001; Evenson, Rosamond, & Luepker, 1998; Humphreys, Hunter, Zimak, OBrien, Korneluk, Cappelli, 2000; Little, Cannon, Whitson, & Jarolim, 1991; Ramm, Robinson & Sharpe, 2001; Waller & Hodgkin, 2000 Education level Cooper et al., 2002; Even son et al., 1998; Humphreys et al., 2000; Ramm et al., 2001 Employment status Brown, Shetty, Delr ahim, Belin, & Leathers, 1999; Evenson et al., 1998; Gucciardi et al., 2007; Hagan, Botti, & Watts, 2007; Ramm et al., 2001 Insurance status Brown et al., 1999; George & Rubin, 2003; Mugavero et al., 2007, Rose and Chung, 2003 Age Cooper et al., 2002; Evenson et al., 1998; Humphreys et al., 2000; George & Rubin, 2003, Gucciar di et al., 2007; Neal et al., 2001; Weinger et al., 2005; Waller & Hodgkin, 2000 Gender Evenson et al., 1998; Mugavero et al., 2007; Neal et al., 2001; Sharp & Hamilton, 2001; Waller & Hodgkin, 2000 Race Brown et al., 1999; George and Rubin, 2003; Humphreys et al., 2000; Mugavero et al., 2007

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17 Family size and composition Evenson et al.,1998; Hagan et al., 2007; Humphreys et al., 2000; Ramm et al., 2001 History of mental illness George and Rubin, 2003; Gucci ardi et al., 2007; Ziemer, Ferguson, Kieltyka, & Slocum, 1998; Hussain-Gambles et al., 2004; Killaspy, Banerjee, King, & Lloyd, 2000; Weinger et al., 2005 Socioeconomic Status and Education Level Across all disciplines reviewed, socioeconom ic status and education levels were corre lated with appointment attendance. Studies of attendance in primary care and general practice found that patients who miss appointments tend to come from lowersocioeconomic class and live in deprived ar eas (George & Rubin, 2003; Neal et al., 2001; Waller & Hodgkin, 2000). Similarly, those who failed to attend cardiac rehabilitation were likely to have fewer years of edu cation and come from lower socioeconomic backgrounds (Ramm et al., 2001; Cooper et al., 2002); while t hose with more years of education were more likely to attend (Evenson et al.,1998). In a study of internal medicine appointment attendance, Little and associates (1991) found that clinics serving lower income populations had higher no-show rates than clinics serving higher income populations. In contrast, Hum phreys et al. (2000) found that non-attendees at a genetics clinic had lower education levels but did not find a significant relationship between income and attendance. Education level may have some beari ng on the patients understanding of the reason for the appointment and understanding of the doctors explanation. Humphreys et

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18 al. (2000), reported that attend ees with higher education leve ls had a better understanding of their reasons for referral. In comparison to non-attendees, attend ees also reported their physician explained the referral better. Limite d finances impact access to transportation or a telephone, no-shows may arise from an individuals inability to cancel or get to the appointment (Sharp & Hamilton, 2001). Employment Status Studies that looked at em ploym ent status and appoi ntment attendance showed mixed results. In a study of attendance at a diabetes self-management program, those who were employed were more likely to be non-attenders. Unemployed individuals were more likely to attend group education than in dividual education. The authors speculated that services offered during standard work hours were inaccessible to some participants who do not want to take time off of work, esp ecially if they are not compensated for that time (Gucciardi et al., 2007). In studies of cardiac rehabilitati on program attendance, patients who were self-employed felt they coul d take as much time off as they needed to participate, while those who were employed by someone else stated employment issues and difficulty taking time off of work were barr iers to attendance (Hagan et al., 2007). In a separate study, going back to work after a card iac event was also reported as a barrier to attendance (Ramm et al., 2001). In contrast to these findings, Evenson and associates (1998) found that being employed was associated with greater utilizatio n of cardiac rehabilitation. Similarly, in a study of attendance for appointments related to orofacial surgery, employed patients missed fewer appointments than unemployed pati ents (Brown et al., 1999). The authors of this study conjectured that employed indivi duals were more likely to have insurance,

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19 which would contribute to improved attend ance (Brown et al., 1999). The varied findings regarding the association of employment status and appointment keeping may reflect the continuity of care that is expected in these se ttings. Diabetes and cardiac rehabilitation programs are more likely to meet regularly, often in sequences of classes or programs. The repeating appointment sequence may be an issue for employed individuals. Insurance Another correlate of attendance is in surance status and type of insurance. Rose and Chung (2003) stated that the strongest predictor of no-show rate was type of insurance, and that those with Medicaid were greater than three times more likely to miss appointments than people in other insuran ce classes. In studies of primary care, individuals who received state funded insu rance, were self-paying, or had less comprehensive coverage were more likely to miss appointments than those who were covered by comprehensive private insu rance (George & Rubin, 2003). Among HIV patients, those with public health insurance were more likely to miss appointments than those with private health insurance (Mugavero et al., 2007). There is likely a triangular relationship between employment status, insurance status, and appointment attendance. Brown and colleagues (1999) reasoned that the unemployed might have more limited access to insurance, which in turn impacts a ttendance. Insurance status appears closely related to employment status as those with more comprehensive health care are more likely to be employed. It is notable that the Veteran possesses a unique combination of receiving comprehensive, federally funded healthcare.

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20 Age Age is a frequently studied correlate of attendance, with varied findings. In the prim ary care/general practice settings, youth is generally associated with non-attendance. In general practice, younger age was associ ated with missed appointments in several studies. George and Rubin (2003) found high rates of no-shows in 17-40 year olds, Waller and Hodgkin (2000) also reported the highest rate of no-shows for doctors was among 20-24 year olds and for practice nurses 034 year olds. Neal and associates (2001) also reported higher rates of missed appointment in young adults In contrast, in a study of attendance at a genetics cl inic there was not a significant age difference in attendees and non-attendees (Humphr eys et al., 2000). In primary care studies, a core population of people who frequently defaulted (defined as more than five no-shows in a year) has been iden tified. This group was disproportionately female and aged 20-34 (Waller & Hodgkin, 2000). However, this study and another by Neal and colleagues (2001) found that the majority of patients who missed an appointment only missed one appointment. In studies of diabetes related appointm ents, the results are more mixed. Weinger et al. (2005) found demographi c characteristics were sim ilar among cancellers and noncancellers for both doctor and nur se practitioner appointments. According to Gucciardi et al. (2007), individuals ag ed 45 years or younger and 65 years of age or older had greater odds of being non-users than thos e who were middle aged. These authors reported older age may be associated with le ss mobility, smaller social networks, and the preference to take a more passive role in health care treatment. In addition, older patients may be incapable or unmotivated to use health resources (Gucciardi et al, 2007, p.

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21 917). There was a more consistent relations hip between age and attendance in cardiac rehabilitation. Evenson and associates ( 1998) reported those betw een the ages of 25-49 were most likely to attend while those being 80 or older least likely to attend. The association of lower attendance with increasi ng age was confirmed in a systematic review of literature related to cardiac rehabilitation attendance (Cooper et al., 2002). Gender Results regarding the impact of gender on appointm ent attendance also are mixed. Sharp and Hamilton (2001) reported non-attenda nce at primary care appointments was higher among males than females In thei r study of missed appointments in general practice, Waller and Hodgkin (2000) reported that 60.7% of no-shows were by women. However, once the higher consultation rate fo r women was controlled for, little gender difference was observed in no-show rates. In another study, the likelihood of missing an appointment was associated with being fe male (Neal et al., 2001). These authors surmised that women may have more appoint ments and as a result miss more than men. In cardiac rehabilitation, men were more likely to attend th an women, with married men more likely to attend than married women (Eve nson et al., 1998). In a separate study of appointment attendance in HIV patients, fema les were more likely to no-show (Mugavero et al., 2007). Race Findings are also m ixed in studies of the relationship between appointment keeping and ethnicity. In their systematic review of non-attendance in general practice, George and Rubin (2003) reported race was identified as a pred ictor in some, but not all, studies. They also noted that studies differ in their categorizat ion of ethnicity. Ethnicity

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22 is a predictor of nonattendance in some studies; but, these studies differ in their categorization of ethnicity. In appointments at a genetics clin ic, ethnicity was not associated with compliance (Humphreys et al., 2000). However, in a study of HIV patients, no shows were more common among racial minorities than Whites (Mugavero et al., 2007). In addition, Brown et al. (1999) found an association between race and missed appointments related to orofacial surgery, Specifically, patients who are unemployed and African American and percei ve themselves as having little social support are at greatest risk for missing recall [follow-up] clinic appointments (Brown et al., 1999, p.408). Family Size and Composition Fa mily size and composition also may influence attendance rates, although the results are mixed. Family structure wa s mentioned most often in the cardiac rehabilitation literature. Those who lived al one were less likely to attend rehabilitation than people who lived with family members who encouraged them to attend (Hagan et al., 2007; Ramm et al., 2001). In a different study, Evenson et al. (1998) reported that married men were more likely to attend than married women. The relationships between attendance and marital stat us and number of children were not statistically significant in a study of appointments at a genetics clinic (Humphreys et al., 2000). However, patients who were planning to have children were mo re likely to keep their appointments. One explanation for the mixed results cen ters on the type of appointment being attended. Cardiac rehabilitation involves significant lifestyle changes relating to diet and exercise patterns that affect other family members, making social support an important feature in the decision to partic ipate and adhere to health pr ovider advice. It also is

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23 possible that some patients, like a person de scribed in a study conducted by Hagan et al. (2007), seek social support by attending group ac tivities, such as a ca rdiac rehabilitation support group, pointing to the complex nature of the causal directi on of the correlation between family structure and attendance rates. In contrast, genetics clinic appointments may be less involved in terms of time and lifes tyle changes, thus family structure plays less of a role in attendance. History of Mental Illness The last correlate of attendan ce is a history of mental illn ess. In their systematic review of attendance in primary care, Geor ge and Rubin (2003) reported that those who missed appointments tended to have more ps ychological problems than those who kept appointments. Weinger et al (2005) reported those who fre quently cancelled doctor or nurse practitioner appointments were more lik ely to have a lower pragmatic/stoic coping style, more anxiety, lower self esteem, more diabetes related distress, more depressive symptoms, and lower self-care adherence (p. 1792). Clinicians and staff of general practice also shared the perception that thos e who missed more appointments also suffered from mental illness (Hussain-Gambles et al., 2004). This was attributed to anxiety and poor concentration l eading to forgetting, confusion, an inability to wait at the surgery, and delusional problems (Hussain -Gambles et al., 2004, p. 111). Depression was also cited as a barrier to attending diabetes appoint ments (Gucciardi et al., 2007; Ziemer et al., 1998). The relationship of me ntal illness and appointment attendance may be best illustrated by reports th at rates of missed appointments at psychiatric outpatient clinics are believed to be double those seen in ot her medical fields (Killaspy et al, 2000).

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24 Determinants of Non-Attendance Num erous studies have looke d at the determinants of appointment attendance, factors reported by patients or pr oviders and clinic staff. In the literature reviewed, four major categories of determinants emerged: cognitive, social, emotional, and structural factors. Cognitive Factors Cognitive factors includ e barriers such as forgetting, perceived importance of the appointment, perceived severity of the c ondition, and lack of understanding of the scheduling system. Forgetting Forgetting was the m ost frequently reported cognitive determinant for missing appointments across several disciplines. Both patients and staff felt that forgetfulness was a common reason for missing appointments in primary care (Hussain-Gambles et al., 2004; Martin et al., 2005). Forgetting was percei ved by staff to be related to age, anxiety, and having "a lot on the mind" (Hussain-Gambles et al., 2004). Almost a third of patients who missed appointments in a gastroenterol ogy outpatient clinic said they forgot (Murdock et al, 2002). Similar results were f ound in studies of no shows in an internal medicine clinic (Little et al., 1991),a genetics clinic (Humphreys et al., 2000), and psychiatric service (Kil laspy et al., 2000). Perceived Importance Perceived importance of the appointm ent is another frequently discussed determinant of attendance. Findings from a study of cardiac rehabilitation illustrate this point well, the participants perception of the programs relevance was found to be

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25 central to whether or not they even entertai ned the idea of attending (Hagan et al., 2007, p. 111). This theme was common to other areas Humphrey et al. (2000) described the relationship of appointment at tendance at a genetics clinic, where patients were less likely to show up because they did not see the appointment as pressing or useful. Specifically, no-shows were significantly relate d to perceived benefits and costs of the genetics appointment (Humphreys et al., 2000). Perceived Severity Although results were mixed, another cognitive determ inant that may influence appointment attendance is the perceived seve rity of the condition. In a systematic literature review of cardiac re habilitation attendance, it wa s reported that non-attenders were more likely to downplay the severity of their illness (Cooper et al., 2002). In contrast, Humphreys et al. (2000) found that perceived severity of the health condition was not related to attendance at a genetics clinic. Perhaps another component of perceived severity of the condition is first accepting the diagnosis and eventually facing the health condition. In a study of appointment keeping behavior at a diabetes clinic, nearly all respondents acknowledged the se riousness of diabet es, the risk for complications, and the importance of c ontinued follow-up. However, a commonly reported barrier to attendance was denial of having the diagnosis (Ziemer et al., 1998). Lack of Understanding The last category of cognitiv e factors that influence appointm ent attendance is patients lack of understanding of the scheduling system. It is reported that patients often do not understand the scheduling system, the im pact of canceling or showing up late, nor the time management or financial implicati ons of failed appointments (Lacy et al., 2004;

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26 Martin et al., 2005). In fact, many patient s perceived non-attendance in a positive light, figuring that these events give providers free time or that maybe they just go to the next patient (Lacy et al., 2004, p.543). Patients believed appointment cancellations happen regularly. In turn, the scheduling system was perceived as flexible and subject to negotiation. Consequently, patients called on short notice to request appointments with the hope that they could be worked into a recently cancelled appointment slot (Lacy et al., 2004). Although some patie nts felt guilty about non-atte ndance, others felt that missed appointments were occasionally to be ex pected and therefore to lerable. Patients may have also felt justified in arriving late to appointments because they often had to wait past their appointment time to see the provider (Martin et al., 2005). Social Factors Social factors include social support, relationship with the provider, and perceived respect betw een patient and provide r. All of these issues have been shown to relate to the results of long waiting times: waiting to be given an appointment and waiting at the medical clinic to see the provider. Respect From the patients viewpoint in the L acy et al. study (2004), "Waiting was one way disrespect was communicated: the patien ts wait to get an appointment time, the patients wait in the waiting room, and the patients wait in the examination room (p.543). As waiting time increased, so did the fee lings of disrespect. Other issues related to respect that contri buted to missed appointments were perceived lack of respect for patients medical history, opinions, and feeli ngs (Lacy et al., 2004). Perceived disrespect may explain why some patients failed to tele phone and cancel. The norm of reciprocity

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27 infers that a person who feels disrespected does not feel obligated to return respect by calling to cancel (Lacy et al., 2004). Social Support Social support offers another way to exam ine the reciprocal relationships between providers and patients. Fa mily influence is a major aspect of social support. Patients who reported that family members encouraged them to attend appointments were more likely to do so, while lack of family support has been reported as a barrier to diabetes appointment attendance (Ziemer et al., 1998) For cardiac rehabilitation participants, family support provided meaning to an indi viduals life, increased their motivation to recover and make lifestyle changes, and pos itively influenced attendance. Family support increased the likelihood of cardiac rehabilitation being an achievable goal. In contrast, those with limited social support did not want to be a burden to others and were more likely to miss scheduled appointments (Hagan et al., 2007). Ramm et al. (2001) confirmed this concept, with the finding that social isol ation was associated with nonattendance in cardiac rehabilita tion. Further support to the importance of social support was found by Killaspy et al. (2000) who repor ted that patients who miss psychiatric appointments were more socially impaired a nd had poorer social functioning. In their study of orofacial injury patie nts. Brown et al. (1999) f ound that strong social support was inversely related to missed appointment s. Patients who perceived more social support were less likely to miss appointment s while those who pe rceived less social support were more likely to miss appointments.

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28 Provider Recommendation and Support Provider recomm endation may al so influence attendance. Humphrey et al. (2000) reported that a strong recommendation by the referring physician has related to improved appointment compliance. These findings were reiterated by Cooper and associates (2002) who also found non-attenders of cardiac re habilitation were less likely to perceive that their physician recommended the progr am. A communicative patient-provider relationship is vital to thei r understanding of recommended treatment and interventions. As stated by Beck and colleagues (2002): A communicative provider-patient relations hip is especially important in the management of chronic diseases, such as diabetes, hypertension, coronary artery disease, and congestive heart failure. When patients ar e informed and involved in decision making, they are more adherent to medical recommendations and carry out more health-related behavior change (e.g., exer cising, smoking cessation, and dietary modification). Such joint deci sion making requires patients to be fully informed about alternatives and potential ri sks of treatment, and to have trust in their physician (p.25). Martin and associates (2005) findings further reiterate th is point. In their study of primary care, patients reported that a lack of empathy and understanding from providers was seen as a barrier to attendance. Patients felt that rapport with their provider was essential. In the same study, medical staff also believed that patients were less likely to attend if a relationship had not been estab lished, although it was clea r that they did not fully appreciate the importance patients pla ced on the doctor-patient relationship (Martin et al., 2005). The relationshi p with the provider is not the only important relationship.

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29 Diabetes clinic patients also reported that perceived negative attitude of clinic staff was also a barrier to attenda nce (Ziemer et al, 1998). Frequent no-shows are likely to have an impact on staff perceptions and attitudes towards those who miss appointments. A qua litative study by Hussain-Gambles et al. (2004) revealed how no-shows influenced staff perceptions of patients in general practice. Patients living in more deprived areas were perceived to lack responsibility and miss more appointments and younger pa tients were perceived to miss more compared with older people, and to be more troublesome by repeatedly missing appointments. They were regarded as having chaotic lives, having short term health problems, lacking respect and responsibilit y, and valuing appointments less than older patients (p. 111). These findings illustrate how no-shows may foster negative relationships between staff and those who frequently miss appointments. Emotional Factors Em otional factors include fear and anxiety surrounding the appointment. Fear and Anxiety Fear and anxiety also are im portant determinants of appointment attendance. Patients reported fear of being seen by a junior doctor was a reason for missing appointment in a gastroenterology clinic (M urdock et al., 2002). In primary care, noshows were higher on return visits when a patient was scheduled to be seen with someone other than their usual doctor. No-shows were also higher among patients seeing practice nurses, medical students, and first year resi dents compared to those visiting doctors (George & Rubin., 2003). Waller and Hodgkin (2000) also reported higher rates of noshows with practice nurses compared to phys icians. Because the JAHVAH is a teaching

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30 facility, these findings are espe cially pertinent. Patients at the JAHVAH are often faced with seeing a variety of health professionals in various stages of training: medical and pharmacy residents, student nurses, social wo rk students, physician assistant students, and dietetic interns. In th e nutrition department, it is a common occurrence for a patient to be seen for an initial appointment by one dietitian or dietetic in tern and attend followup with a different person. Fear of medical procedures and findings also were reported as barriers to attendance. For some participants, negativ e anticipation of the visit outweighed the potential benefits of attendan ce. Participants faltered when they were concerned about undergoing uncomfortable procedures (Lacy et al., 2004). As one participant in this study stated, I said, Nope, Im not going! Thats uncomfortableso I just didnt come (p. 543). Another quote from a patient (Lacy et al., 2004) highlight s fear of the unknown as a barrier to attendance, Im scared they might tell you something, some bad newsCome in with a headache and they say youve got a big brain tumor up there I dont want to go back, I dont wa nt to hear no bad news (p.5 43). The negative impact of anxiety and stress on appointment attendance was also confirmed with diabetes appointments (Weinger et al., 2005; Ziemer et al., 1998). Structural and L ogistical Factors Logistical is sues associated with sche duling and attending appointments also may affect no show rates. Structural/Logistical issues include long wait times, difficulty scheduling, competing priorities, costs, t ype of provider, and transportation.

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31 Wait Times In addition to conveying disrespect, l ong wait times are am ong many structural determinants that influence appointment atte ndance. Across all disciplines, patients voiced frustration related to long wait times a nd reported long wait ti mes as a barrier to attendance in primary care (Martin et al., 2005) diabetes clinics (Ziemer et al., 1998), and psychiatric appointments (K illaspy et al., 2000). Finally, longer wait times also were associated with failure to establish car e in HIV patients (Mugavero et al, 2007). Long wait times negatively impact patient satisfa ction. As satisfaction declines, so does appointment attendance. Patients were more likely to miss an appointment when many days had passed between scheduling and the ac tual date of the appointment (Lacy et al., 2004). Although not explicitly cite d in the literature, personal interviews and discussions with VA staff indicate three reasons long wait ti mes are likely to decrease attendance: 1) the patients are more likely to forget about the appointment as the wait time increases; 2) a patient is more likely to attend when the c onversation with the provider is fresh in their mind; and 3) concern about the nutrition relate d health condition is lik ely to fade as days between the phone call or scheduling of the appointment and the date of the actual appointment increase. Difficulty with Scheduling System The next structural factor that influences appointm ent attendance is difficulty with the scheduling system. In primary care clinic s, cancellation difficulty was reported as a major issue (Hussain-Gambles et al., 2004). Patients reported difficult communication, such as busy telephone lines, difficulty in contacting scheduling cl erks, and failure to receive appointment notices as barriers to attendance (Martin et al., 2005; Ziemer et al.,

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32 1998). Another barrier to attendance for cardi ac rehabilitation patients was inconvenient scheduling (Ramm et al., 2001). Lastly, gastroen terology patients also perceived clerical error as a reason for missed a ppointments (Murdock et al., 2002). George and Rubin (2003), illustrate how se veral structural barriers to attendance can be interrelated: Appointment systems can be a barrier to health care, and non-attendance may be a reflection of difficulty of access to se rvices. Where there are problems in accessing health care, waiting lists for appoi ntments get longer and this in turn leads to increased non-attendance. Appointment systems may be difficult to use for members of communities in areas of so cial deprivation or low socio-economic class. Some patients have less predictable, chaotic lifestyles that are not easily compatible with a structured system (p.180). Problems related to telephone communication is especially pertinent in this study because the JAHVAH uses a phone based schedu ling system. In addition, many of the JAHVAH patients are snowbirds, or transients, who live in Florida for the winter months and return home, typically to Northern regi ons for the summer months. Having patients that live in another region for one half of the year can complicate phone communication. Also, inconvenient scheduling also may be of concern for working Veterans. Currently, the JAHVA has limited primary care access, as the majority of primary clinics have appointment availability on wee kdays between 8:00am and 4:00pm. Competing Priorities Long waits and lim ited clinic hours may be li nked to the next st ructural barrier competing priorities and conflicting events. The first competing priority is difficulty

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33 taking time off of work. In a study of attendance in primary care, employment competed for patients time and contributed to no-show s (Martin et al, 2005). Humphreys et al. (2000) did not find an association between taking time off from work and appointment attendance. However, respondents who were not paid for time taken off from work were more likely to miss appointments than t hose who were (Humphreys et al., 2000). Other types of schedule conflicts were repo rted as barriers to attendance. Simply being too busy has been reported as an obs tacle (Humphreys et al., 2000). In several studies, the most common reasons for non-attendan ce, after forgetfulness, were family or work obligations (Little et al., 1991; Sh arp and Hamilton, 2001; Ziemer et al., 1998). Having to arrange childcare was a commonly re ported family care issue that was a barrier to attendance (Humphreys et al., 2000; Sharp & Hamilton, 2001). Diabetes patients also reported scheduling conflicts like other hea lth care appointments (Ziemer et al., 1998). In addition to scheduling conflicts, othe r common barriers reported by cardiac rehabilitation and diabetes patients were financial costs related to appointment attendance, medications, and transportation (H agan et al., 2007; Ziemer et al., 1998). Transportation problems also were reported as barrier to attendance in a different study of cardiac rehabilitation (Ramm et al., 2001). It is notable that "tra nsportation problems" may infer matters other than cost, including is sues such as reliable personal or public transportation or perhaps relying on fam ily members for transportation. Findings regarding transportation were not consistent Humphreys et al. (2000) did not find a significant association between appointment attendance and mode of transportation in their study of appointment k eeping at a genetics clinic.

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34 Additional transportation concerns, such as driving distan ce and convenience of facility location may play important roles in appointment attendance. In a study of appointment behavior in HI V patients, no shows were more common among those who lived outside of the coverage area (Mugavero et al., 2007). Rose and Chung (2003) also reported that location and convenience of the hea lth care facility influenced attendance. Transportation issues are especially pertinen t to Veterans. Many Veterans drive from distant and surrounding areas to attend appoint ments at JAHVAH, they deal with limited parking, and increasing fuel prices while living on fixed incomes. Other Two re maining factors that do not readily fit into the categor ies discussed above are also important: feeling too unwell and feel ing better. Feeli ng too psychiatrically unwell was one of the most common reasons for missing follow-up psychiatry appointments (Killaspy et al., 2000 ). Internal medicine pa tients also reported missing appointments because of feeling too unwell. Conversely, symptoms may improve and the patient may feel like the a ppointment is no longer necessar y (Lacy et al., 2004). This finding was confirmed by the results of Little et al. (1991), whose participants reported missing appointments because of feeling better. General practice providers and clinic staff also felt that patients missed appoi ntments because of feeling better (HussainGambles et al., 2004). Nutrition Specific Three studies related to nutrition appointm ent or program attendance were found in the literature. The first study assessed factors associated with attendance in a voluntary nutrition education program for women served by the Special Supplemental

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35 Nutrition Program for Women, Infants, and Ch ildren (WIC). The authors used surveys and focus groups to gather demographic info rmation and patients reported reasons for failing to attend. The results of this study indicated that the relationship between attendance rates and ethnicity and attendance ra tes and marital status were statistically insignificant. Participants in this st udy reported the following reasons for failed attendance: no longer participating in WI C, moving, competing priorities, negative feelings about nutrition education, and lack of transportation or childcare (Damron, Langenberg, Anliker, Ballesteros, Feldman, & Havas, 1999) The second study was a brief intervention study to investigate the impact of reminder phone calls on attendance at a diabetes outpatient clinic in Ireland (Finucane, Gaffney, Hatunic, Burns, & Nolan, 2007). Th is study found that phone calls were helpful in improving attendance rates. Forty-three percent of pa tients in the observation group (no reminder) attended while 63% of patients who received a reminder call attended. Demographic variables such as age, weight, blood sugar control, and body mass index were similar in attenders and nonattenders (Finucane et al., 2007). The third study examined the reasons diab etic patients do not attend appointments with their dietitian. This study was conducted in the Netherlands where referrals to the dietitian occur as a standard course of prac tice in a multidisciplinary health care team. The authors gathered information regarding pos sible determinants of failed appointments through qualitative research consis ting of a literature review, interviews with specialists, dietitians, diabetic nurses and internists, a nd patients. The interview findings informed the development of a telephone survey.

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36 The results of this study indicated that non-attendees of nutrition appointments also were more likely to no-show with their doctor or nurse than attendees. The demographic characteristics of marital state, social class, education level, and sex were not significantly associated w ith attendance. Findings indi cated that those born outside of the Netherlands were less likely to attend than those from the country. Mean BMI was higher in non-attendees than attendees. Seve ral psychosocial variab les were related to attendance. Non-attendees perc eived fewer diabetes-related risks, greater difficulty in attending appointments with dietitian, less oblig ation to attend the appointment, and lower efficacy of dietary advice. Patients also reported forgetting, having a stable body weight, and feeling that the nutrition appointment was not us eful. Study authors stressed the importance of helping patie nts understand they can contri bute to their own health and the belief that improved marketing of dietit ian services and different approaches to address clients are needed (Spikmans, Brug, Doven, Kruizenga, Hofsteenge, & van Bokhost-van der Schueren, 2003). Although these three studies examined popul ations that differ significantly from Veterans in the United States, they provide insights about factors affecting nutrition appointment attendance. Of special interest are findings that negativ e feelings associated with attending dietitian appointments and a pe rception that they w ould not learn anything new may be salient in this study. Conclusion Many factors have been identified th at influence appointm ent attendance. Predictors of non-attendance include: social economic stat us and educational level, employment status, insurance status, age, gender, race, family size and composition, and

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37 history of mental illness. Reasons for missing appointments include cognitive, emotional, social, and logistical/structural barriers. These factors interrelate with demographic factors to cont ribute to non attendance. Despite the extensive research that ex ists on appointment attendance, further investigation is needed to better understand nutr ition appointment attendance in the Veteran population. This study will examin e what reasons Veterans report for nonattendance to nutrition appointments and which factors are correlated to attendance. This proposal seeks to conduct research from a gr ounded theory perspectiv e, contributing to current knowledge by addressing existing gaps in the lite rature regarding nutrition appointment attendance in the Veteran population.

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38 CHAPTER 3 METHODS Introduction This chapter describes the research m e thodology and includes six major sections: (1) a review of the studys research questi ons and purpose; (2) st udy design; (3) survey and interview instruments; (4) analysis and data management; (5) strengths and limitations; (6) hypotheses. Purpose & Research Questions The purpose of this study was to iden tif y factors that influence nutrition appointment attendance in the Veteran population. The results of this study will be used to identify ways to reduce no shows for nut rition appointments at the James A. Haley Veterans Hospital. The im pact of increasing nutrition appointment attendance includes: improved access to nutrition appointments, mo re efficient use of resources, improved management of nutrition related conditi ons, and improved patient satisfaction. The study was designed to answ er the following questions: Research Question 1: What reasons do Vetera ns report for non-atte ndance for individual nutrition appointments? Research Question 2: What factors are correlated with appointment non-attendance for nutrition appointments at the VA?

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39 Study design This study utilized a sequential m ixed methods design. Individual interviews were followed by a mail survey. Semi-structure d interviews were used to explore views regarding non-attendance, its causes and impact. The mail survey examined the relationship between these factors and attendance. Individual interviews have been found particularly useful in gathering feedback fr om the patient and provider points of view. As described by Martin et al (2004) interviews provide the opportunity to gather information from a purposive sample, until a saturation of themes is reached. A mail survey was chosen for the quantitative porti on because of its relatively low cost, the anonymity provided by mail surveys, and the el imination of interviewer bias. These methods have been used in many previous st udies of appointment attendance (Brown et al., 1999; Humphreys et al., 2000; Hussein-Gambles et al., 2004; Lacy et al., 2004; Little et al., 1991; Martin et al., 2005; Mur dock et al., 2002; Spikmans et al., 2003). Population and Sample The sam ple was drawn from the outpatient population of the JAHVAH main ambulatory care clinics. The clinic population is predominatel y male and older than 55. To be eligible for the study, Veterans were scheduled for a nutrition appointment during the preceding 30 days of the phone interview or mail survey. In the Ambulatory Care population, nutrition appointments most often originate with re ferrals from the patient's primary care provider. Patients are predominately referred for weight management, hyperlipidemia, hypertension, and diabetes. A mi nority of patients is seen in outpatient nutrition clinics for issues such as gastroin testinal disorders, sw allowing difficulty, or loss of weight related to disease treatment or status such as HIV or cancer.

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40 Sample Selection In addition to having been scheduled fo r an appointm ent within the previous month, to be included in the study Veterans were also classified as ambulatory care patients, between the ages of 18-79, enrolled for VA health care, and receiving primary care at JAHVAH to be included in the study. Non-Veterans, those aged 80 and older, patients of the women's center, CBOC patients, and patients of the diabetes, internal medicine, and geriatric clinics were exclude d from the study. Individuals aged 80 and older were excluded as the majority were likel y to receive their care through the geriatric clinic. The women's center has a separate dietitian who is staffed to cover women's center nutrition appointments. Nutrition appoi ntments in the women's center account for 11-13% of all outpatient nutriti on appointments. The diabetes and internal medicine clinics are considered specialty clinics whose patients are likely to have more complicated health issues and are beyond the scope of the primary care setting. The CBOC clinics are typically located in more rural areas and patients of these clinics receive their primary care off of the JAHVAH campus. Sample Size Interview Sample Veterans selected to participate in th e study were drawn from patients who had been scheduled for outpatient nutrition appoi ntm ents in the main ambulatory care clinics of JAHVAH. A purposive sample was selected based on the matrix outlined in Table 6 and included only individuals whom the principl e investigator had not previously seen for individual appointments or cl asses. A one-month retrospect ive appointment history list for appointments that were scheduled for December, 2008 was used to begin sampling.

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41 Interviews began during January, 2009. Sa mpling continued through mid January and interviews were conducted through the end of January 2009. Although the following matrix served as the basis of the sampling plan, the strategy of theoretical saturation determined the final number of interviews Table 7 summarizes the final interview sample. Table 6 Interview Sampling Matrix: Minimu m Sampling Estimates by Age Group 18-44 45-64 65+ Attended appointments 2 2 2 Failed to show 4 4 4 Total 18 The sampling matrix included three ag e groups. Eighteen to 44 years olds represent a population segment that is likely to have recently departed from the military given than age of enlistment is 18 years of age, and 20 years of service is considered a full military career. Individuals forty-five to 65 years of age represent those who are more likely to have been separated from the military for a significant time period but have not yet reached retirement age. Although the focus of this research was nonattendance, interviews were also conducte d with attendees to provide a basis for comparison. The majority of individuals s een in ambulatory care are above 45 years of age. The interviews conducted with the 18-44 year age group di d not add significantly new or different findings than those in terviewed from the older age groups.

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42 Table 7 Actual Interview Sample 18-44 45-64 65+ Attended appointments 2 3 3 Failed to show 1 5 3 Total 17 Survey Sample Historical attendance data provided insight to the poten tial sample population for survey collection. Tab le 8 outlines attendance patterns for ambulatory care nutrition during selected months of 2007. Table 8 Historical Attendance Data, 2007 March April May June July Aug Attendance 297 278 253 260 247 257 No-shows 62 45 63 40 115 57 Cancellations 157 141 99 79 111 160 Total 516 464 415 379 473 474 Cancellations represent a signifi cant proportion of potentially failed appointments. To further investigate attendance patterns of thos e who cancelled, a chart review of 100 patient scheduling records wa s conducted to inves tigate the scheduling patterns of those who cancel. Of the 100 charts reviewed, 25 of these appointments were

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43 cancelled by the clinics for va rious administrative reasons. The other 75 were cancelled by patients. Of the 75 that were cancelled by patients, 39 reschedul ed and later attended the nutrition appointment. Given the variance within the cancellati on group, they were not included in the survey sample. Only people who failed to show or attended were interviewed or mailed surveys. Sample size calculations (based on power of .8, alpha of .05, a baseline attendance rate of 70% and an od ds ratio of 2.0) determined that a sample size of 288 was sufficient to provide statistically significant results. Data Collection Interviews One week prior to calling individuals, a pre-no tification letter was mailed to potential participants. The le tter outlined the purpose of the study, privacy information, and provided an opt-out option. Semi-structured interviews were c onducted by telephone on JAHVAH premises. Interviews were audio recorded only when participants granted permission to do so. One individual did not grant permission. Intervie ws were conducted within 1-30 days of the scheduled nutrition appointment. Informed consent was obtained verbally. See Appendices B and C for a copy of the pre-no tification letter, r ecruiting script, and interview guide that were used for this study. Surveys To optim ize the response ra te, surveys were distribut ed using concepts from Dillmans tailored design method (2000). Th is method entails sending personalized prenotice letters prior to distribution of the que stionnaire, mailing questionnaires by certified mail with postage pre-paid return enve lope, incentives, reminder post cards for

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44 unreturned questionnaires, and thank you postcards for completed questionnaires (Dillman, 2000). A pre-notice letter, incentives and certified mail were not used. Token incentives were not feasible, and certified mail would have contributed to increased subject burden in a population that may have limited mobility and transportation. In a previous study of appointment attendance, Hussain-Gambles and associates (2004) obtained a 74.9% response rate using pre-pa id return envelopes and second and third reminders. Elements of the Tailored Design Method (Dillman, 2000) were used to establish the time sequence for mailings. For the fi rst mailing, potential subjects were mailed a survey and cover letter with in 14 to 30 days of their scheduled appointment. Approximately one week later, a thank you/ reminder postcard was mailed. In keeping with Dillmans (2000) recommended timeline, those who failed to respond were sent a second letter and the complete survey packet approximately three week s from the date of the first mailing. Recruitment occurred between mid-March and mid-July. Initially, surveys were mailed to 207 attenders and 55 non-attenders who had been scheduled for appointments within the previous month. Surveys were then sent on a more frequent basis to people who had been scheduled the past two weeks. Post card and second survey mailing were sent to these participants though June 2, 2009. Because the volume of attenders who retu rned the survey was far more abundant than non-attenders, several strategies were a dopted to obtain an ade quate sample of nonattenders. For appointments occurring from mid-April to the end of May, smaller batches (4 to 10 surveys) were mailed within one to two weeks of the scheduled appointment (70

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45 surveys) to non-attenders only. Second, in an attempt to improve the response rate, a handwritten note in contrasting ink was added to the cover letter that accompanied surveys (approximately 41 surveys). Fina lly, the IRB granted permission to place a reminder phone call after the mailings to encour age non-attenders to return the survey (52 surveys). These strategies resulted in an adequate number of responses from nonattenders by mid-July, at which poi nt recruitment was terminated. Instrumentation Existing literature on appointm ent attendan ce was used to inform the development of the semi structured interview guide and draft survey instrument. See Appendices C and D for a list of study variables and inte rview guide. Interview questions were designed to elicit patient opinions related to appointment attendance, with follow-up questions related specifically to their most recently scheduled nutrition appointment. Nutrition-specific questions focused on: how the appointment was scheduled, reasons for missing/attending the appointment, expectations and feelings rela ted to the nutrition appointment, social influences (healthcare team or family members), and suggestions for improving appointment attendance. Interview questions addressed certain demographic variables including: size of hous ehold, employment status, e ducation level, insurance, and income. For sampling purposes, scheduli ng records were used to identify gender, age, and if the scheduled appointment was an initial or follow-up appointment. The mail questionnaire drew on qualitative interview results as well as results from previous studies. The initial surve y, or draft instrument, included history of appointment attendance, reported reason for not attending, social support, perceived importance of the appointment, perceived effect iveness of the appointment, health status,

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46 understanding of the scheduling system, and demographic variables. Answer format included multiple choice and likert scales. The draft survey was piloted during the interview phase. Interviews brought to light topics were not previ ously on the interview guide and nullified previous topics of interest. Several variables were added and deleted from the original instrument. A summary of these changes are outlin ed in Table 9. The final list of survey variables is listed in A ppendix D. The survey and related mailings are included in Appendices E through H. The revi sed survey instrument was resubmitted to the IRB for approval before administration. Dillmans Tailored Design Method (2000) was used in the survey format and layout. The goal was to develop a questionnaire instrument that looked appealing and important. A usable, easy to manipulate, format is intended to reduce costs to the particip ant, and facilitate trust (Dillman, 2000).

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47 Table 9 Survey Changes Added Variables Deleted Variables Appointment attendance History (ever attended) Attitude towards appointment Memory Parking time Parking difficulty Perceived difficulty attending appointment because VA is too busy Perceived trust of VA healthcare vs. civilian healthcare Reminder letter/call was split into two separate Questions Schedulingability to request convenient time Scheduling systemperceived ease of use Service connected disability Transportation difficulty Way finding Weather Who referred patient to nutrition appointment Patient understands reason for Referral Perceived obligation Perceived need Travel distance Transportation mode

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48 Data Management All data collected were s tored in a lock ed file cabinet. Electronic data were password protected. Interview recordings were destroyed after transc ription. Participant confidentiality was maintained by avoiding use of patient names/identif iers in reports and on surveys and by using non-identif ying participant codes for data analysis. In keeping with the Dillman Tailored Design Method (D illman, 2000), a list of people who were mailed a survey and those who responded were maintained until data collection was complete. The list was destroyed when recruitment ended. Data Analysis Interviews Qualitative data was analyzed us ing the constant comparative analysis method (Strauss & Corbin, 1990). Interviews were audio recorded and key quotes transcribed. Themes were identified using concepts of the long-table approach, as described by Krueger and Casey (2000). This approach is a low-technology option that includes literally cutting key quotes from the transcript and pasting them into another document to identify themes and categories (Krueger & Casey, 2000). Attender and non-attender results were then summarized in two separate documents. Similar responses to interview questions were grouped together to identify themes. Attender and no-show results were pl aced in a spread sheet and reviewed to eliminate duplications. Themes were then so rted into the constructs indentified in the literature review. Finally, the variables and constructs indentified in the interviews were compared to the original list of variables. Themes and concepts that emerged from interviews informed the revision of survey questions.

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49 Surveys Descriptive statistics were perform ed to provide an initial summary of survey responses and to determine the completene ss of the survey responses. Appendix I provides a summary of missingness by questi on. Appendix J summarizes descriptive statistics for demographic variables. Surv ey results were then evaluated, eliminating missing data, by Chi-square, Fishers exact tests, and t-tests to make comparisons between non-attenders and atte nders to determine significan t variables for constructing the regression models. A p value of .05 was used to determine the statistical significance of results. Chi-square and Fishers exact tests were used for categorical non-ordinal dependent variables, while t-tests were used for continuous dependent variables (BMI and age) as well as ordinal dependent variable s (income, education, likert scales). T-tests on ordinal variables provided insight as to the differences betw een attender and nonattender mean scores. Lastly, the hypotheses were tested with binary logistic regression using SPSS statistical software. Regression was chosen so that significan t variables could be controlled for while testing each hypothesis vari able. In the regression model, criterion and explanatory variables were continuous, cat egorical, or both (A gresti, 1996). As in the bivariate analysis, the criterion, or depe ndent, variables were classified according to attendance at the previous appointment: 1) non -attenders 2) attenders. The regressors (predictor variables) included significan t variables from the following categories: demographic, cognitive, stru ctural, and social factors. Demographic and sociopsychological variables that were determined to be significant with t-test and chi-square analyses were controlled for in the hypothe sis testing. These va riables included prior

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50 attendance history, insurance status, perceive d health, income, perceived importance of the appointment, and BMI. The null hypothesi s stated appointment attendance occurred independently of predictor variables (age, income, sati sfaction with care, etc). Hypotheses 1. Perceiv ed family support will be positively associated with nutrition appointment attendance after controlling for significan t demographic and socio-psychological factors. 2. Perceived importance of the nutrition appoi ntment will be positively associated with nutrition appointment attendance after controlling for significant demographic and socio-psychological factors. 3. Perceived expertise of the dietitian as a health professional will be positively associated nutrition appointment attenda nce after controlling for significant demographic and socio-psychological factors. 4. Perceived provider encouragement will be positively associated with nutrition appointment attendance after contro lling for demographic and sociopsychological factors. 5. Veteran participation in the referral pr ocess will be positively associated with nutrition appointment attenda nce after controlling fo r demographic and sociopsychological factors.

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51 CHAPTER 4 RESULTS Introduction The purpose of this study was to identify the factors that influence Veterans determinants of nutrition appointment at tendance at the James A. Haley Veterans Hospital. This study used a mixed methods de sign to answer two research questions: 1) What reasons do Veterans report for non-attendance for individual nutrition appointments? and, 2) What factors are correla ted with appointment non-attendance for nutrition appointments at the VA? This chapter presents the findings of th is study, beginning with a description of the study sample, reasons Veterans gave in individual inte rviews for missing appointments and results of logistical regres sion analyses of survey data to identify factors correlated with appointment attendance. Interview Sample Veterans who did not show for the nutri tion appointm ent are referred to as nonattenders and those who attended the nutrition appointment are referred to as attenders. Interview respondents were intentionally selected to repres ent attenders and nonattenders in specific age range s, with 2 attenders and 1 nonattender between 18-44 years, 3 attenders and 5 non-attenders between 45-64 years, and 3 attenders and 3 non-attenders aged 65 years or older.

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52 Reasons for Missing Appointments Veterans reported the following reasons for m issing or having difficulty attending nutrition appointments: competing demands, feeling too poorly to go, transportation problems, scheduling problems, forgetting, e xperience with past appointment, knowledge not new or useful, negative att itude toward VA, and lack of social support. This section reports on interview findings for cognitive, structural, and social variables related to nutrition appointment non-attendance. Structural The following section s ummarizes interv iew findings related to structural variables and nutrition appointment attend ance: competing demands, difficulty with transportation, and scheduling barriers. Competing Demands Interview participants identified several competing priorities as barriers to appointment attendance. Work conflicts were a commonly reporte d reason for missing nutrition appointments. Several scenarios were presented to illustrate how work interfered with appointment attendance. Working several jobs was a common barrier. As a 43 year old Veteran reported One reason I miss appointments is, a couple Ive had to reschedule, is that I work the equivalent of 3 jobs. The prospect of losing income was another problem that inte rfered with appointment k eeping. As a self employed Veteran stated, Lets suppose Ive been scheduled for an appointment at Tuesday at 11:00, and I have a job. I would have to decide for myself will I give up the income to attend

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53 the appointment. I dont have the opportuni ty to make money like young kids do. So if it comes down to it, Ill earn the money. Some Veterans reported that retirement status provided more flexibility in scheduling and attendance. The impact of retirement was summarized by a respondent who had recently retired from the military this way: For those of us in the retired status, it s easier than when I do go back to work. At that point, its going to be almo st impossible to make them [nutrition appointments]. Right now since Im in an almost pure retirement status, my flexibility is what makes it easy. Family care such as caring for a child, s pouse, or parent was also reported. Respondents reported caring for sick childre n, ailing spouses, and being primary care givers to elderly parents. Another reason appointments were missed wa s due to travel. For example, one respondent missed his nutrition appointment becau se he was out of town traveling for the holidays. Transportation difficulty Transportation difficulty was another co mmonly reported barrier to attendance. Transportation issues included tr avel cost, travel distance, difficulty with transportation, needing to make special travel arrangements parking, inclement weather, and difficulty navigating the building and VA grounds. The cost of gas was of concern to many Veterans. Travel distance and sharing a vehicle were a challenge fo r others, as a 48 year old non-attender reported, I share a vehicle and I live about 20 miles away, it's hard for me to get there if I don't have a vehicle ." Another individual described the travel

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54 difficulty of his car breaking down, and the ne ighbor that was going to give him a ride was drunk and unable to bring him. Other Veterans had to make special travel arrangements such as scheduling for a VA van in advance. Limitations of the VA van schedule also posed barriers to attendance, "I guess having it scheduled at the right timesome of them, a lot of guys ride vans and can only be there in the morning but some clinics are in the afternoon." Or as another individual put it, "Like the van I ride in, we catch it about the same place you do the city busit's 5 miles for me to catch the vanusually I have to get somebody to get me there." JAHVA is an expanding facility, with a challenging parking situation. When asked, What makes it difficult to attend nutrition appointments, one of the most common responses was summarized by this statement: For those who are driving, it's parkingbig time. In the last several years patient s and staff parking has decreased as new construction has edged into lots previously allocated to parking. To address this situation, the VA provides complimentary vale t parking and offers a shuttle from a neighboring shopping mall where patie nts and staff can park in a satellite lot and take a bus to the VA. This quote from a 60 y ear old attender sums up the situation well, "They are doing valet parking now, it's still the valet line gets backed up, you have to wait. If it gets too long, you have to go down to the mall and then you have to wait on transportation from the mall back to the hospital and you can be late for your appointment or actually mi ss ityou are spending so much time just trying to get in the building. Now I just ta ke the city busy instead of dealing with parking.

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55 Inclement weather was also reported as a reason for non-attendance. Heavy rains common in the summer time can greatly aggravate the transportation and parking challenges mentioned above. Finally, difficulty navigating the VA facili ty and grounds was identified as reason for missing appointments. Interview respondents indicated the building is large, and it is easy to get lost. For those with limited m obility, long walks are a challenge and at times there are not enough wheelchairs availabl e. As one individual described, everybody gets lostit's a given that you are dealing with this miasma, y ou arrive a half hour early to figure it out. Another respondent simply stated Getting lost in the buildingthey have so many different clinic sif they don't come in the ma in entrance it's easy to get lost. These respondents indicated that when an individual gets lost they may be late for, or miss the appointment. Scheduling Difficulty Som e participants reported that they missed appointments when they had not had a chance to participate in determining the appointment day and time. Respondents stated appointments were often made automatically, a letter would arrive in the mail, and they were not asked if that date and time were acceptable. Several respondents explained why this practice is such an inconvenience, The VA sets an appointment and doesn't co ntact usfor example I get assigned appointments without my input. Maybe a fternoon appointments are better for me, but I get stuck with morning appointments.

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56 The important thing is to have a say in what time the appointment is made. I would like to have more input into it, if they would have called me and said hey what to do you think about this date . That would have been helpful. The heavy volume of patients seen at the VA was also mentioned as a deterrent to attending appointments. Patients reported that doctors were so busy that their previous clinic appointments with them ran later th an scheduled, overlapping with their nutrition appointments scheduled on the same day. One Veteran described the problem this way: Its so many people there, and it seems like they are overbooked at times for appointments, or appointments run over. And then if you are running behind on your first appointment, then most people te nd to try to just make it, if they have a lot of appointment, make it an al l day affair. But if you are late for that first or second one, then that just bumps everything down the line." Interview respondents indicat ed that receiving appoint ment reminders promoted attendance while difficulty with the reminde r system was a barrier to attendance. Respondents indicated varying levels of consistency with reminders. Some felt reminders were plentiful and consistent as a 74 year old non-attender stated, They remind us when we are checking out, we get a reminder card, and phone calls. That should be enough. However, other respondents indicat ed they did not get consistent reminder phone calls or that appointment remi nder letters arrived da ys after the actual date of the appointment. Interview results suggested that failur e to understand the scheduling system may impact appointment attendance. A 65 year old attender explained his dislike for the system and difficulty hes observed,

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57 "The ridiculous method that as I am le aving the appointment I have a follow up appointment that is currently for three months, but the appointment they make me is not the appointment that is made. I w ill get a notice that I need to call and make the appointment. As logic goes, this is absolutely pathetic. I was there last Wednesday, there was this older couple there in their 70's, who had an appointment but they didn't have an appoi ntment and they couldn't figure out what that was. They were supposed to call in at that time to make the appointment. And they said that made no sense to them." Feeling Unwell A variable that falls within its own cat ego ry is feeling too unwell to attend the appointment. As this non-attender explained, "Sometimes you actually f eel too bad to go, you gotta realize I'm 66, I've had a stroke, I'm not in the greatest shape in the worldmy blood pressure is too high, or I'm dizzy. My stroke left me feeling di zzy a lot of the time I don't trust getting in the car and driving when I feel that way." Cognitive Interview results indicated several cognitive factors related to nutrition appointment attendance. Forgetting Interview respondents commonly reported forgetting as a reason for missing their nutrition appointment. Statements th at reflect this finding include: I got my dates mixed up. Sometimes I flat out forget.

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58 I say yep I'm going to be there and th e appointment is for 2:00 and 2:30 get's here and I say, oh shit." Experience with Past Appointment During interviews, participants were as ked to describe their feelings about attend ing nutrition appointments. Their responses varied widely, from positive comments about looking forward to the appoint ment, to indifference and disinterest. Those who looked forward to the appointment often referred to positive experiences with previous nutrition sessions or success that resulted from fo llowing the dietitians advice. One 66 year old Veteran who regular ly attended appointments stated, The education is very helpful, I learn more every time I see the nutritionistI was looking forward to going. One Veteran acknowledged having his or iginal skepticism changed by the help he received: My mind was closed, I'm set in my wa ysI came in thinking I'm not going to listen to them, and I found it started making sense." Many Veterans who expressed disinterest, ambivalence, or negative attitudes toward s nutrition appointments also referred to previous appointments, but their experiences had not been as helpful. Knowledge Not New or Useful A closely related factor is Veterans per ception of dietitians advice. Interview results revealed that Veterans had widely varying levels of perceived dietitian knowledge or expertise. Som e regarded the dietitian as an expert in nutrition and a valuable health care team member. Others believed the di etitian doesnt know mu ch more they do and will not tell them anything they dont already know Those who did not feel they were getti ng new or useful information and did not find additional appointments necessary. As one individual described,

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59 You know, if thought I was going to get some thing out of it that I didnt have before I went there.I feel like, you know, like you can probably get all that information in one good sitt ing instead of having to get one piece at time or something. I dont think they know all that much. I mean they tell you to reduce your calories and your salt. I mean, I guess they could recommend things to eat and things not to eat Others felt the dietitian gave them a dvice that was impractical to follow, The problem is that they want me to eat things I cannot afford. Those who felt the dietitian provided ne w or useful information were more satisfied and reported coming back for additiona l appointments. As one individual stated, I like it. I always enjoy talking to her She always explains everything in detail. I know she is telling me right.I like the dietitians advice. She's got more knowledge than me. The more I attend, the more I learn. Another individual stated, I learned new things I didnt expect to. She approached it in a logical, realistic approach. Some Veterans attributed their good attendan ce record to the impact previous sessions had had on their health status. "I look forward to itfor one I am seei ng a lot of progress, I've seen a whole bunch of progress in the weight loss, I've come down from 210 to now I'm 158, I'm very close to the 155 I'm shooting at.I was very pleased with that. And then through the dietitian I got involved in the MOVE program, so now I lift weights and do a lot of cardio. So I've seen a big improvement in just my body composition. It's kind of great to look in the mirror because I see muscles now.

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60 I'm very satisfied with the results. Ever yone is working as team. I just look forward to all of my appointment because it is working for me." Others did not necessarily feel they were learning new information, but did continue to attend because nutrition appointme nts helped them stay on track and increase accountability. As simply stated by a 61 year old attender, "In a roundabout way I knew what I should have been doing, this was just reinforcement. Another reported he went to appointments to just basically to get more ideas, more reit eration, someone else that is really in the field of nutrition, as dietitians do act ually tell me what I already knew, they reinforced it, but hearing it from somebody else made is easier to make changes. Attitude Toward VA Attitud es towards the James A. Haley Veterans Hospital were also discussed as a factor influencing appointment attendance. Varying attitudes towards VA care were reported by interview respondents. Some had negative feelings, reflected in distrust. One Veteran admitted that his feelings were quite negative, because he figured that this was the latest gimmick. That the government that some bureauc rat somewhere had this idea and they were now having to spend a couple million dollars from congressI figured that I knew that I knew everything that anybody ever had to know [about nutrition] Others reported positive feelings toward s the VA and higher levels of trust. A common theme was that VA culture was familiar after years of military service and that the VA better understands the healthcare needs of Veterans. As a 45 year old non-

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61 attender stated, I did just short of 26 years in, the VA to me, seems more what Im used to . Another reflected that the VA better understands the healthcare needs of Veterans, I would have to say in terms of trust; in the VA they have your best interest at heart because you are a Veteran. They real ly do a lot, to help you and they have a lot more generalized things to help you with ultimately the many problems you face, as a combat vet, or ju st a regular vet. They personal ize it a little more. I'll give you a good example. Say you have PTSD If you go to the emergency room [non-VA] for a PTSD issue, you might s it there for 10 hours before they get you in, and then what are they really going to tell you. They are going to tell you, here take these drugs, or here is this prescription, go sleep it off. Where if you went to the VA they will direct you in the right areas to get you the proper care you need, say as a combat vet with PTSD. Social Interview participants id entified lack of social support as a reason for nonattendance. In contrast, social support encouraged attendance and came from many sources including health care pr ofessionals and family members. A 61 year old attender summarized who encouraged him to attend, Several people, my primary care doctor, my wife, myself of course ." Family Support Interview respondents reported varying leve ls of social support from family. Social support ranged from none whatsoev er and no one to stronger levels of support. Spouses and adult ch ildren were identified sources of support. Spouses often attend nutrition appointment with the Veteran. However, this practice is not always seen

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62 as supportive, the 29 year old attender reported that his wife attended the appointment but it wasnt really encouragement, it was more knowledge on her part since shes the main cook. In contrast, another individual stated th at his wife attends appointments with him and reminds him of the importance of eati ng well and attending nutrition appointments. Provider support Lack of provider support was another so cial factor in non-attendance. Som e respondents did not recall receiving a referra l from their provider for a nutrition appointment. In a few cases, participants re ported that a nutrition appointment had been scheduled automatically, and they learned about the referral from a letter in the mail or when a clerk scheduled them for an appointment as they were checking out for the doctor appointment. I'm under the assumption the doctor want s me to gobecause I get these appointment reminders in the mail. "I was referred by my doctor; they sent me a date and time I wasn't able to make. So, I cancelled that appointment and told them I would reschedule at a later date. And then they automatically rescheduled me again, which I never even knew about. And then the doctor had called me and told I missed the appointment and so then I rescheduled for a time that I was able to be there." Other Veterans reported that their providers had encouraged them to talk with a nutritionist and referred them to the nutrition clinic. Provider support ranged from simply telling them an appointment was needed to strongly recommending a nutrition consult and/or deciding together if it w ould be helpful. Patients perceptions of discussions with their providers also varied. Some de scribed these as open and helpful. She said I

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63 needed to lose some weight and (a sked) would I like to have some help ." Other respondents indicated that th e conversation was stern, and was less of a recommendation and more of an order. A 63 year ol d attender put it in these terms, I respect his opinion, that's why I we nt. We sat down during an appointment and he said the only problem I had was my cholesterol. And he said he was going to schedule me. If he would have asked me, I would have said no. If I get a letter, I go." Another stated, yes...he said that you need to see a nut ritionist and then he stated one or two reasons why, and I said yes sir. This individual describes the importa nce of the doctors encouragement, "What would get them to attend appointme nts is the doctor; stress how important it is for them. Especially we can do a ll we can with medications, but if you are not eating right, then the medications and stu ff then that's just trying to take care of the symptoms. The doctor needs to stress just how important the nutrition meetings are so you can get your diet right. Because some people don't care about diet, just give me my medicine." When asked about social support, interv iew respondents also responded that they were their own source of encouragement or mo tivation. This concept was expressed with comments such as "No, I wanted to do this myself. The doctor left the decision up to me and I'm self motivatedit's me. In summary, interview results identified multiple reasons why Veterans do not keep nutrition appointments. These factor s included competing demands, feeling too poorly to go, transportation problems, sche duling problems, forget ting, experience with

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64 past appointment, knowledge not new or useful negative attitude toward VA, and lack of social support. These results were used to design the mail survey. The following section reports significant findings from the survey analysis. Survey Response Rate The overall response rate for attenders a nd non-attenders is summarized in Table 10. Reponses rates for non-attenders varied slig htly as new recruitment strategies were employed. The overall response rate for attenders was 66%. The following response rates apply to non-attenders. The response rate for individuals who received the first mailing without a note or phone call within two to four weeks of the scheduled appointment was 27.7%. The response rate fo r individuals who received the first mailing without a note or phone call within one to two weeks of the scheduled appointment was 30%. The response rate for surveys that in cluded a personal note a nd were mailed within one to two weeks of the scheduled appointme nt was 24%. Finally, the response rate for surveys that included a personal no te and a reminder phone call was 33%. Table 10 Survey Response Rate Attender Non-attender Responded 267 82 Did Not Respond 138 162 Response Rate 66% 33%

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65 Survey Sample A total of 349 individuals re turned the survey. Of these respondents, only 3 were female. Females were excluded from the surv ey analysis because of the small number and inability to generalize to the female Veteran population. For the remaining 346 respondents, demographic characteristics are summarized below and are fully outlined in Appendix J. Mean age of respondents was 59 years (ranging from 2-79 years). Mean BMI was 30.4 (ranging from 14.6-55.5). Seventy-eight percent lived in households of two or more people. Forty eight percent did not have insurance outside of VA hea lthcare, 505% received VA disability, and 21.3% received non-VA disability. Nearly 58% of respondent s were married. Only 21% reported their health status as very good or excellent, with remaining resp ondents rating their health as good, fair, or poor. Nearly 30% of respondent s had completed high school, 43% attended some college, and 21% had completed colleg e or beyond. The majority of respondents were not employed, with 74% reporting being out of work, retired, or unable to work. Fifty eight percent reported inco me of less than $25,000 per year. Survey Results The f ollowing tables summarize the statistical analysis of survey data. Table subheadings indicate the construc t category for each set of vari ables. Each test examined the correlation between the following inde pendent variables and attendance, while examining differences between attenders and non-attenders. The ta bles are followed by a discussion of the results.

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66 Table 11 Significant Survey Results Demographic variables Statistical test pvalue Effect size Attendeda Did not attendb Previous nutrition appointment attendance 2 .001 .186 70.43 49.33 Private Insurance 2 .011 .140 54.65 37.84 Health Status t-test .011 .339 3.16 3.49 Incomec t-test .047 .230 4.16 3.49 BMI t-test .039 .277 30.79 28.94 Cognitive variables Forgot about appointment 2 <.0001 .421 94.70 60.81 Satisfaction with dietetic care t-test .007 .434 1.20 1.49 Perceived Importance of appointm ent t-test .013 .336 1.26 1.49

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67 Understanding of scheduling systemimpact on other Veterans t-test .04 .282 1.34 1.57 RD knowledge t-test .020 .306 1.16 1.32 Social variables Family support t-test .014 .341 2.51 2.98 How referred 2 d .018 .202 37.16 34.67 Structural variables Reminder call 2 <.0001 .245 78.49 52.63 Reminder letter 2 .002 .176 89.6 75.32 Convenient time 2 <.0001 .314 92.06 66.22 Travel 2 <.0001 .246 97.7 84.62 Weather 2 <.0001 .226 98.11 87.01 Difficulty with transportation 2 <.0001 .288 94.34 73.42

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68 Family care 2 <.0001 .265 96.21 79.45 Feeling well enough to attend 2 <.0001 .281 91.83 68.92 Cost 2 .011 .138 95.4 87.34 Parking time 2 d .027 .158 78.57 68.52 Preferred Day 2 d .022 .154 73.09 65.75 Note: for 2, effect size = Cramers V, for ttest effect size = Cohens d. aFor 2 tests indicates proportion that attended, for t-test indicates mean score on an ordinal scale of 1-5 for attenders, in 2d indicates proportion of attenders for modal category. bFor 2 indicates proportion that did not attend, for t-test indicates mean score on an ordina l scale of 1-5 for non-attenders, in 2d indicates proportion of nonattenders for modal category. cIncome was measured on an 8 point scale 1 being <$10,000/year, 8 being above $50,000/year. dIndicates 2 with Fisher option.

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69 Table 12 Non-significant survey results Demographic variables Statistical test pvalue Effect size Attendeda Did not attendb Employment on day of appointment 2 .707 .020 78.03 80.00 Wait days t-test .914 .017 2.79 2.78 Travel time t-test .324 .131 1.77 1.88 VA Disability Status 2 .365 .050 51.98 46.05 Non VA disability Status 2 .824 .012 78.54 77.33 Marital Status 2 d .493 .116 58.73 53.25 Household size 2 d .501 .085 47.22 40.26 Age t-test .132 .197 59.97 58.18 Education t-test .082 .229 4.82 4.61 Employment 2 d .052 .169 36.51 32.89

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70 Cognitive variables Appointment expectations t-test .578 .093 2.03 2.12 Looked forward to appointment t-test .579 .074 1.53 1.59 Understanding of scheduling-impact on dietitian t-test .843 .029 3.38 3.42 Trust VA more than civilian healthcare t-test .807 .032 1.93 1.90 VA better understands health care needs t-test .303 .135 1.89 1.75 Social variables Who referred 2 d .814 .082 84.23 80.00 Provider support t-test .896 .018 1.88 1.86 Structural variables Wait days t-test .914 .017 2.79 2.78

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71 Travel time t-test .324 .131 1.77 1.88 Parking difficulty t-test .114 .207 3.02 2.71 VA too busy t-test .830 .029 3.69 3.65 Scheduling System t-test .114 .29 1.67 1.89 Way finding t-test .875 .02 4.07 4.05 Note: see notes for above table Demographic and Other B ackground Characteristics Prior Nutrition Appointment Attendance In survey respondents, attenders appeared m ore likely th an non-attenders to have previously attended a nu trition appointment. Seventy percent of attenders had previously attended a nutrition appointment, while on ly 49.3% of non-attende rs had previously attended a nutrition appointment. Chi-square analysis revealed significant differences in prior attendance ( p=.001, effect size .186). Insurance Statistical analysis indica ted insurance status was si gnificantly different among attenders than non-attenders. Attenders were more likely to have private insurance: 54.7% of attenders had private insurance co mpared to 37.3% of non-attenders. Chisquare analysis was statistically significant ( p=.011, effect size .140). Health Status Although this variab le was not explicitly discussed in interviews, it was included in the survey because of its importance in other studies (Payne, et al., 2005). T-test

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72 analysis revealed that attenders reported si gnificantly different health status than nonattenders ( p =.011, effect size .339). Attenders were mo re likely to better rate their health than non-attenders. Forty three percent (mode) of attenders rated their health as good while nearly 38% (mode) of non-at tenders rated their health as fair. On a scale of one to five (excellent to poor), mean health status was 3.16 for attenders and 3.49 for nonattenders. Income There was a statistically significant diffe rence in the reported income level of attenders and non-attenders (p=.047, effect size of .230). In come was measured on an 8 point scale, with 1 being <$10,000 per year, and 8 being above $50,000 per year. On this scale, mean income was 4.2 for attenders a nd 3.5 for non-attenders. Descriptive statistics indicated that nearly 55% of non-attenders have an annual income of less than $25,000 per year, while 44.6% of attenders have inco me in the same range. Similarly, 14.2% of attenders have an income above $50,000 a nnually while 9.8% of non-attenders have income in the same range. BMI One of the most frequently reported reas ons for nutrition appointment attendance was for weight management or weight relate d conditions. Descriptive analysis indicated that mean BMI was similar for attenders and non-attenders. Mean BMI was 30.8 for attenders (range 14.6-55.5) a nd 28.9 for non-attenders (range 17.6-51.7). T-test results reflected significant differences in BMI for attenders and non-attenders ( p =.039, effect size .277).

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73 Cognitive Forgetting Chi-square analysis indicated strong statistical significance ( p <.0001, with an effect size of .421). Forty percent of non-attenders reported forgetting their appointments. Satisfaction with dietetic care T-test analysis of satisfaction with dietetic care also indicated a statistically significant differences between attenders and non-attenders (p =.007, effect size .434). Attenders were more likely to report higher satisfaction levels th an non-attenders. Perceived importance of appointment Whereas large proportions of both gr oups agree that attending nutrition appointments was important to their health, at tenders were more like ly to strongly agree while non-attenders were slightly more likely to agree somewhat that appointments are importance ( p=.013, effect size .336). Understanding of scheduling system-impact on other Veterans Survey analysis suggest that responden ts understood the impact of no-shows on fellow Veterans but were less clear on how it impacted VA staff. There was a significant difference between attenders and non-attende rs on their understanding of how missing an appointment impacts other Veterans ( p=.04, effect size .282). Attenders were more likely than non-attenders to agree that missing an appointment will mean fewer appointments are available for other Veterans. There was not a significant difference in how either group viewed the impact of missi ng appointments on dietitians.

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74 RD knowledge T-test analysis for perceived knowledge of the dietitian was statistically different between attenders and non-attenders ( p =.020, effect size of .306). This question asked survey respondents to rate thei r belief that a dietitian is a knowledgeable source of health information on a strongly agre e to strongly disagree scal e. While large proportions of both groups agreed with this statement, th e attenders were more likely than those who missed appointments to strongly agree. Social Family support T-test analysis revealed significant difference for atte nders and non attenders for perceived fam ily support ( p=.014, effect size .341). There wa s not a significant difference in attendance by marital status. As a group, at tenders reported higher levels of family support than non-attenders. Provider Support and Referral There was not a significant difference be tween attenders and non-attenders in the likelihood that a provider had referred them for a nutrition appointment. The majority (80-85%) of respondents reported that a docto r referred them. However, differences between attenders and non-attenders in how the Veteran viewed the referral process was significant ( p= .018, effect size .202). Twenty eight percent of attend ers reported that they decided together with their doctor compared to only 17.3% of non-attenders..

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75 Structural Reminder calls and letters Re minder calls ( p <.0001, effect size .245) and reminder letters ( p=.002, effect size .176) also appear to impact appointment attendance. Nearly seventy nine percent of attenders reported ge tting a reminder call compared to only 52% of non-attenders. Similarly, nearly 90% of attenders reported getting a reminder letter compared to 75% of non-attenders. Convenient time Veterans ability to participate in setting an appoint ment time was significantly different between attend ers and non-attenders ( p <.0001, effect size of .314). Nearly 92% of attenders reported that they were able to request a convenient time compared to 66% of non-attenders. Weather Weather had statistically si gnificant relationship with appointment attendance. Although this variable was significantly correlated with attendance behavior ( p<.0001, effect size .226), very few non-attenders (10 out of 78 responses) indicated that bad weather interfered with keeping their appointment. Transportation Non-attenders were more likely to repor t difficulty with transportation to the appointment ( p<.0001, effect size .276) than attenders. Twenty six percent of nonattenders reported difficulty with transporta tion compared to 6% of attenders.

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76 Cost Non-attenders were more likely to report th at the cost of the nutrition appointment (for example cost of gas, or co-payments) kept them from attending. Nearly 13% of nonattenders reported difficulty with cost compared to 4.6% of attenders ( p =.011, effect size .138). Parking Reports of parking problems were wide spread: Nearly 79% of attenders and 68.5% of non-attenders reported th at parking took less than 30 minutes. However, the relationship with attendance is weak. Despite a significant p -value, the effect size was quite small ( p =.030, effect size .155). Preferred day Survey respondents were asked to identif y the preferred time (morning, afternoon, or evening) and day of the week (weekday or Saturday) for appointments. Statistical analysis revealed significant differences in the appointment day and time preferences for attenders and non attenders (p=.022, effect size .154). Sevent y three percent of attenders and 65.8% of non-attenders preferred a ppointments on weekdays. Although nonattenders were slightly more likely than attenders to pref er weekend appointments, the number of individuals indicati ng this preference (7) was quite small. It may be worth noting that for both attenders and non-atte nders, 24% indicated no preferences between weekdays and weekends. Competing Demands Attendance correlated with both co mpeting priorities of travel ( p<.0001, effect size .246) and need to care for a family member ( p<.0001, effect size .265). Fifteen

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77 percent of non-attenders reported being out of town or traveling and 20.5% reported family care as a barrier to appointment attendance. Feeling Unwell Chi-square analysis indi cated a significant difference for attenders and nonattenders on feeling well enough to attend ( p<.0001, effect size .281). Nearly 69% of non-attenders reported feeling well enough to attend on the day of the appointment compared to 92% of attenders. Hypothesis Testing Binary logistic regression was used to test the following hypothesis statements, while controlling for significant demogra phic and socio-psychol ogical factors: Hypothesis One: Perceived family support will be positively associ ated with nutrition appointment attendance. Hypothesis Two: Perceived importance of th e nutrition appointment will be positively associated with nutrition appointment attendance. Hypothesis Three: Perceived expertise of the dietitian as a health professional will be positively associated nutrition appointment attendance. Hypothesis Four: Perceived provider encouragement will be positively associated with appointment attendance. Hypothesis Five: Veteran participation in the referral process will be positively associated with nutrition appointment attendance. Significant demographic and socio-psychol ogical factors were determined during bivariate analysis and include d: prior attendance history, insurance status, perceived

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78 health, income, perceived importance of the appointment, perceived provider support, perceived family support, and BMI. In each regression model, attendance was the dependant variable. Family support, perceived importance of the appointment, perceived knowledge of the dietitian, perceived provider encouragement, and participation in the referral proce ss were the indepe ndent variables. Regression results The following tables summarize regression re sults. Table 13 shows the variables that remained significant in th e regression models. Ranges of p values reflect a summary of results for all 5 regression models used for hypothesis testing. Table 14 summarizes hypothesis testing. The dependent variable in each regression is appointment attendance. Under each hypothesis, the independent variable is indicated by bold font. Results for control variables included in each re gression model are also displayed. Table 13 Significance of Control Variables in Regression Models Variable p value in regressions Past attendance history .002-.005 Health status .006-.009 Family Support .029-.038 BMI .046-.067 Insurance .075-.090 Perceived Importance .053-.189 Provider Support .576-.778 Income .800-.898

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79 Table 14 Logistic Regression Results Hypothesis 1a Hypothesis 2 b Hypothesis 3c Hypothesis 4 d Hypothesis 5e Variable B S.E. Sig B S.E. Sig B S.E. Sig B S.E. Sig B S.E. Sig Past attendance history .987 .313 .002 .987 .313 .002 .900 .319 .005 .987 .313 .002 .975 .313 .002 Insurance .545 .319 .087 .545 .319 .087 .545 .322 .090 .545 .319 .087 .585 .329 .075 Health status .453 .172 .009 .453 .172 .009 .490 .177 .006 .453 .172 .009 .452 .173 .009 Income .015 .058 .800 .015 .058 .800 .008 .059 .898 .015 .058 .800 .014 .058 .806 BMI .048 .025 .058 .048 .025 .058 .051 .025 .046 .048 .025 .058 .047 .026 .067 Family Support .227 .109 .038 .227 .109 .038 .241 .110 .029 .227 .109 .038 .236 .110 .032 Provider Support .038 .135 .778 .038 .135 .778 .078 .140 .576 .038 .135 .778 .039 .135 .771

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80Perceived Importance .330 .171 .053 .330 .171 .053 .244 .186 .189 .330 .171 .053 .327 .172 .057 RD knowledge .323 .248 .192 Veteran participation in referral process .021 .130 .872 Note: bolded values indicate variables for hypothesis test. a Perceived family support will be positively associated with nutrition appointment attendance. bPerceived importance of the nutrition appointment will be pos itively associated with nutrition appointment attendance. cPerceived expertise of the dietitian as a health professional will be positively associat ed with nutrition appointment attendance. dPerceived provider encouragement w ill be positively associated with appointment attendance. eVeteran participation in the referral process will be po sitively associated with nutrition appointment attendance.

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81 Hypothesis One: Perceived family support will be positively associ ated with nutrition appointment attendance. This hypothesis was accepted: The relationship between family support and attendance was statistically significant, indicating that those with increased family support had higher odds of attending than those that did not ( p =.039, Odds Ratio= 1.3). Hypothesis Two: Perceived importance of th e nutrition appointment will be positively associated with nutrition appointment attendance. This hypothesis was rejected: There was not a statistically significant correlation between perceived importance of the nutrition appoint ment and nutrition appointment attendance when controlling for other variables. Hypothesis Three: Perceived expertise of dietitian as health professional will be positively associated nutrition appointment. This hypothesis was rejected: There was not a statistically significant correlation between perceived expertise of th e dietitian and nutrition a ppointment attendance when controlling for other variables. Hypothesis Four: Perceived provider encourag ement will be positively associated with appointment attendance. This hypothesis was rejected: There was not a statistically significant correlation between perceived provider encouragement and nutrition appointment attendance when controlling for other variables.

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82 Hypothesis Five: Veteran participation in the referral process will be positively associated with nutrition appointment attendance. This hypothesis was rejected: There was not a statistically significant correlation between Veteran participation in the referral process and appointment attendance when controlling for other variables.

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83 CHAPTER 5. DISCUSSION & CONCLUSION Introduction This chapter includes a d iscussion of the results for each research question. It is organized into the following sections: research summary, discussion of results, strengths and limitations of the study, implications fo r future research, and implications for improving nutrition appointment attendance. Research Summary This study s ought to identify factors that influence nutrition appointment attendance and to use these findings to identify strategies for reducing the no-show rate for nutrition appointments and improve the ab ility of the JAHVAH to provide nutrition services to Veterans. Bene fits of increasing nutrition a ppointment attendance includes: improved access to nutrition appointments, mo re efficient use of resources, improved management of nutrition related conditions and improved patient satisfaction. The following research questions were addressed: What reasons do Veterans report for non-attendance for individual nutrition appointments? What factors are correla ted with appointment non-attendance for nutrition appointments at the VA? The study design entailed sequential use of qualitative and quantitative methods. Individual, semi-structured interviews were used to identify factors associated with

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84 outpatient nutrition appointment attendance. Seventeen individuals were purposively selected to represent appointment attende rs (8 individuals) and non-attenders (9 individuals) in the following age groups: 18-44, 45-64, and 65 and older. Individual interviews were analyzed using the constant comparative analysis. Results informed the development of a survey instrument that was mailed to a sample of Veterans to examine the relationship between appointment keeping and potential determinants identified in the qualitative portion of the study and literature review. To obtai n a statistically significant sample, mail surveys were sent to individuals drawn from the clinics attendance and noshow reports and continued until 349 individu als responded. Logistic regression analysis was performed on survey results to identif y correlates of appointment attendance. Research Summary Interviews revealed num erous cognitive, structural, and logistical reasons for missing appointments. These barriers and others reported in the litera ture were included in the mail survey. Bivariate comparisons of attenders and non-attenders revealed significant relationships between appointment keeping and the following variables: past nutrition appointment attendance, non-VA in surance, health status, income, BMI, forgetting, satisfaction, perceived importance, understanding of scheduling system, RD knowledge, family support, how referred, reminde rs, input to appointment time, travel, weather, difficulty with transportation, fam ily care, feeling well, cost, parking time, and preferred day. Regression analyses suggest that only pe rceived family support, past attendance history, health status, and BMI remained correlated with appointment keeping when

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85 controlling for other variables. As result, Perceived family suppor t will be positively associated with nutrition appointment attendance is the only hypothesis accepted. Discussion of Results There were m any similarities and differen ces in this studys findings and those found in the literature. Results of this study are similar to previous studies that found family support (Brown et al., 1999; Hagan et al., 2007; Killaspy et al., 2000; 2007; Ramm et al., 2001; Ziemer et al., 1998), patient-provider communication (Beck et al., 2002; Cooper et al., 2002; Hum phrey et al., 2000; Martin et al., 2002 ), having private insurance (Brown et al., 1999; George & R ubin, 2003; Mugavero et al., 2007; Rose and Chung, 2003) and perceived importance (Hagan et al., 2007; Humphrey et al., 2000) were positively associated with attendance. Also consistent with previous studies, lower income level (George & Rubin, 2003; Neat et al., 2001; Waller & Hodgkin, 2000) and forgetting (Humphreys et al., 2000; Hussain-Gam bles et al., 2004; Killaspy et al., 2000; Martin et al., 2005; Little et al., 1991; Murdock et al., 2002) are associated with nonattendance. In contrast to previous findings, this study did not find th at education level (Cooper et al., 2002; Evenson et al., 1998; Humphreys et al ., 2000; Ramm et al., 2001) or long wait times (Lacy et al., 2002; Killaspy et al., 2000; Martin et al ., 2005;Ziemer et al., 1998) were associated with attendance. Othe r demographic variables that were identified in the literature were not signi ficant in this study, including em ployment status (Brown et al., 1998; Evenson et al., 1998; Gucciardi et al., 2007; Hagan et al., 2007; Ramm et al., 2001), age (Cooper et al., 2002; Evenson et al., 1998; Humphreys et al., 2000; George & Rubin, 2003, Gucciardi et al., 2007; Neal et al., 2001; Wein ger et al., 2005; Waller &

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86 Hodgkin, 2000), gender (Evenson et al., 1998; Mugavero et al ., 2007; Neal et al., 2001; Sharp & Hamilton, 2001; Waller & Hodgkin, 2000), and family size (Evenson et al.,1998; Hagan et al., 2007; Humphreys et al., 2000; Ramm et al., 2001). Social The relationship of social support and a ppointm ent attendance was an important finding of this study. Social support is multif aceted and includes many different types of support: emotional, instrumental, informa tion, and appraisal (Coreil, Bryant, and Henderson, 2001). Interview respondents indicated trust in th eir physicians and encouragement from family members were sources of emotional support. Interview respondents also reported rece iving useful health information and advice from their primary care providers and dietitians as s ources of support. Family members also demonstrated instrumental support by assis ting with appointment scheduling, providing transportation, grocery shopping, an d preparation of meals. The vast majority of Veterans reported th at they were referred to the nutrition appointment by their primary care provider. Surprisingly, differen ces between attenders and non attenders in perceived provider support were not statis tically significant. Study results indicate that non-attenders and attend ers were similar in who referred them to appointments. However, patients participati on and ownership in the process is important to nutrition attendance. Those who reported deciding together with their physician, and those who were able to request a time that was convenient were more likely to attend. Surprisingly, marital status was not statistically associated with attendance. Also, there was a significant difference in social support from fam ily and friends. However, interviews suggest that verbal and emoti onal encouragement and assistance with food

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87 choices and preparation by spouses are impor tant in making nutrition related lifestyle changes. Structural Difficulty parking at the VA was not a significant predictor of attendance. However, further discussion of this variable is warranted as this problem was reported by many Veterans. Interview results, as well as personal experience, indicate that the parking situation is a very frustrating ordeal for anyone visiting JAHVAH. Interview responses indicated that many individuals negotiate the parking situation by planning head and allowing extra time for parking. A llocating additional time for parking may reflect increased motivation for atte nding nutrition a ppointments. Although scheduling preferences was also excluded from the regression models, findings for this variable may have impli cations for practice. To determine if appointments are currently being offered at convenient days and times, interview and survey respondents were asked to identif y their preferred time of day (morning, afternoon, or evening) and day of the week (weekday, or weekend) for appointments. Interview respondents indicated a variety of preferences. Surv ey analysis indicated that 24% of both attenders and nonattenders indicated no pref erence between weekday and weekend appointments. Results from this study and the literature suggest that providing reminders is also helpful (Sharp & Hamilton, 2001; Hardy, OBr ien, & Furlong 2001). In this study, 58% of non-attenders received a reminder call compar ed to 78% of attenders. Ninety percent of attenders and 76% of non-attenders received reminder letters. Clearly, receipt of a reminder is related to appointment attendance. However, it is difficult to surmise why

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88 one group is more consistently getting reminders than the other. Those who are not receiving phone or mail reminders may not ha ve consistent phone service or accurate addresses in the system. This trend was not ed when attempting to contact non-attenders for interviews, with non-working phone numbers and returned mail. Study Strengths This study benefits from the combination of qualitative and quantitative data. Qualitative information was used to inform the collection and interpretation of quantitative data. This study also contributes unique information to the literature as, at the time of this writing, it is the only rese arch identified that examines non-attendance of nutrition appointments at a VA facility. This study was conducted in the setting of the nation's largest single payer he althcare system. Although results may not readily transfer to the private healthcare industry, the study results may contribute to improved understanding of nutrition appointments in a he althcare system that serves millions of Veterans. Limitations Methodological Difficulties Several m ethodological difficulties may have affected study results. Because the survey was self-administered, the ability to clarify questions or probe was lacking, and it was not possible to ensure that the Vetera n answered each question unaided by others. Another limitation stemmed from the use of the telephone for interviews, making it impossible to observe body language, facial ex pression, and other visual cues that may have lent insights to attendance barriers. It also was impossible to examine gender differences because the vast majority of patie nts in the selected clinics were male.

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89 Finally, the survey only included two que stions on social support, one question related to family support and one questions related to provider support. Given the small number of questions on this variable, limited insight may be drawn from the results of this study. Bias Selection bias resulted f rom mailing surv eys which may have been less appealing to younger Veterans than web-based or tele phone surveys. Utilization of phone and mail contacts also missed homeless individuals. Non-response bias also applied. Whether ag reeing to participate in interviews or to complete a mail survey, those who responde d were likely to be different from those who did not. It was hoped use of the Tailored Design Method (Dillman, 2000) would enhance the response rate and minimize the im pact of response bias. However, it is important to acknowledge that 47% of individuals chose not to respond, and it was not feasible to compare respondents with non-resp ondents to examine th e source of response bias. Social desirability also may have affected findings. This may have been enhanced by the fact that the researcher introduced herself as a VA employee as well as a USF student. As a result, the pa rticipants may have felt less inclined to answer candidly knowing that the researcher was a VA employee. Although information was kept in strict confidence, participants may not have fully trusted my promise. Social desirability may also be reflected in how survey respondent s rated their satisfacti on with care. Many noshows marked that they were satisfied with their appointme nt despite having apparently missed the appointment.

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90 Because of the researchers personal involvement with the nutrition department and clinical care of Veterans, at times it was difficult to clearly delineate the role between researcher and VA dietitian. Because of th e researchers knowledge of the VA system, there were times research subjects became patients. Such as one individual who had questions for his dietitian before his next fo llow-up. The researcher was able to put him in touch with his dietitian so that his questi ons could be answered in a timely manner. To enhance reflexivity, the researcher kept a br ief journal of her t houghts and reactions to the interviews. This helped maintain object ivity and supported a process that encouraged participants to voice their opi nions as freely as possible. Chance Because of the larg e number of outcome variables being examined, multiple comparisons in this study could have led to false positives. This is possible for variables that were significant, yet had smaller e ffect sizes (<.2), incl uding previous nutrition appointment attendance, insurance status, how referred, reminder letter, cost, parking time, and preferred day of the week. External Validity This study has lim ited external validity due to the unique nature of the VA health care system in comparison to the general public. Improving the study design to include women, younger Veterans, and pa tients of major hospital centers as well as small community clinics would improve validity within the VA system. Recommendations for Future Research Future studies of nutrition attendance in the Vetera n population are needed to confirm this studys results. Because we re underrepresented in this study and are

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91 entering the VA healthcare system at increasing rates, this study should be replicated to include these populations. In future resear ch, women should be interviewed to identify any additional barriers to attendance or potential differen ces between male and female Veterans in reasons for missing appointments. With this input, th e survey instrument should be revised and adapted to an internet survey. Shifting from mail to a web-based survey may be more appealing to younger Veterans. Although social support was found to be si gnificantly relate d to appointment attendance in this study, further investigation of this topic is needed due to the limited number of survey questions that were used to measure this construct. To expand on the analysis of the relationship of support and a ppointment attendance, the survey instrument should be revised to include several questions on this topic. Established instruments such as the The Social Support Appraisals Scale (SS-A) (Vaux, et al., 1986) and the Perceived Social Support-Friends/Family (PSS-Fr/Fa) (Procidano and Heller, 1983) provide depth and insight to further measur ement of social support. Implications The relationship of social support and appointm ent attendance have several implications for primary care providers and registered dietitians. Because of the important role family members play in providing instrumental, informational, and emotional support, spouses and family members should be included in the nutrition counseling process starting at the initiation of the referral. In cluding spouses in the scheduling process could facilitate instrume ntal support in terms of transportation and appointment arrangements. Inviting and encouraging family members to attend

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92 appointments and providing spouse/family sp ecific education material would also promote further instrumental and informational support. To enhance informational social support received from primary care providers, the nutrition department should provide training and information to VA physicians, encouraging them to focus on the importance of nutrition appointments when referring patients to the dietitian. The patients social situation also should be considered when referring Veterans to nutrition programs. The referring provider should seek input from the patient as to their desired level of support, this information may help guide the patient towards individual appointments or group classes. Study findings also have implications for the management of James A Haley nutrition counseling services. For instance, results suggest th at attendance would improve if patients were allowed to select a ti me and date for the next appointment. Lack of input as to day and time of the appointme nt was consistently re ported as a barrier to attendance by non-attender inte rview participants and rein forced with the bivariate analysis. In similar fashion, patient involvement in the referral process is likely to improve nutrition appointment attendance. Study findings also suggest that income level is a potential barrier to attendance. As a result, referring providers should be sensitive to transportation and communication costs of attending appointments, and dietiti ans should be sensitive to income related restrictions on dietary choices when providing advice. Find ings related to preferred appointment time do not necessitate creating we ekend nutrition clinics. However, results indicate Veterans may be willing to attend Saturday nutrition appointments if they were

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93 offered. Piloting a weekend nutrition clinic may provide further insight as to the utility of this intervention. Currently, reminder calls are initiated th rough an automated system. However, the automated system calls only the primar y phone number. Personalized reminder calls may be improved if both home and cellular num bers are called. Interview results also indicated that some Veterans received their reminder letter after the date of the appointment. Veterans also i ndicated that without their prio r knowledge of the referral, appointment letters arrived auto matically. Because of lack of input as to the appointment time, many individuals had to call in and reschedule their appointment. Specific strategies for addressing these and other barriers to appointment keeping have been discussed in th e literature. Rose and C hung (2003) suggest an open-book appointment method, modified wave method, an d appointment reminder system. Double booking is another strategy. However, as noted by Izard (2005) and Sharp and Hamilton (2001), the potential for staff fr ustration and decreased patient satisfaction is great. In practice, the above interventions are not likely appli cable within the VA. Strategies such as the open-book appointment method and m odified wave method would likely be frustrating to staff and Ve terans as respondents indica ted that attendance problems occurred when various health care appointme nts ran too close together. As noted by Izard (2005), serving on a first come first served basis also creates long waits.

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94 REFERENCES (NHANE S) National Health and Nutriti on Examination Survey. (1999-2000). Agha, Z., Lofgren R.P., VanRuiswek, J.V ., & Layde P.M. (2000). Are patients at Veterans Affairs medical centers sicker? Archives of Internal Medicine 160(21): 3252-3257 Agresti, A. (1996). An Introduction to Categorical Data Analysis. New York: John Wiley & Sons, Inc. American Diabetes Association, Direct and indirect costs of diabetes in the United States. Retrieved on December 8, 2007 from http://www.diabetes.org/diabetesstatistics /cost-of-diabetes-in-us.jsp American Dietetic Associati on (1995). Position of the Amer ican Dietetic Association: Cost-effectiveness of medical nutrition therapy. Journal of the American Dietetic Association 95(1), 88-91. American Dietetic Associat ion (2001). Strategies for improving follow-up client appointment-keeping compliance. Journal of the American Dietetic Association 101(8), 935-939. American Heart Association, Cardiovascular Disease Cost Retrieved December 8, 2007 from http://www.americanheart.org/presenter.jhtm l? idintifier=4475

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95 Arterburn, D.E., McDonell, M.B., Hedric k, S.C., Diehr, P., & Fihn, S.D. (2004). Association of body weight with condition sp ecific quality of life in male Veterans. The American Journal of Medicine, 117 738-746. Beck, R.S., Daughtridge, R., & Sloane, P.D. (2002). Physician-pati ent communication in the primary care office: A systematic review. Journal of the American Board of Family Practice, 15 (1), 25-38. Brown, E.K.A., Shetty, V., Delrahim, S., Belin, T., & Leathers, R. (1999). Correlates of missed appointments in orof acial injury patients. Oral Surgery, 87(4), 405-410. Center for Disease Control. Prevalence of Overweight and Obesity Among Adults: United States, 2003-2004. Retrieved December 8, 2007 from http://www.cdc.gov/nchs/products/pubs/pubd/hestats/overweight/overwght_adult_03 .htm Center for Disease Control. QuickStats: Prevalence of Obesity* Am ong Adults Aged > 20 Years, by Sex --National Health and Nutrition Examination Survey (NHANES), United States, 1999--2000 Through 2003. Retrieved December 8, 2007 from http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5544a7.htm Cooper, A.F., W einman, J., & Horne, R. ( 2002). Factors associat ed with cardiac rehabilitation attendance: a system atic review of the literature. Clinical Rehabilitation 16, 541-552. Coreil, J., Bryant, C.A., Henderson, J.N. (2001). Social and Behavioral Foundations of Public Health Thousand Oaks, Sage Publications, Inc. Damron, D., Langenberg, P., Anliker, J., Ballesteros, M., Feldman, R., & Havas, S.

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96 (1999). Factors associated with attendance in a voluntary nutrition education program. American Journal of Health Promotion 13(5), 268-275. Das, S.R., Kinsinger, L.S., Yancy, W.S., Wa ng, A., Ciesco, W., Burdick, M., & Yevich, S.J. (2005). Obesity prevalence among Ve terans at Veterans affairs medical facilities. American Journal of Preventative Medicine, 28(3), 291-294. Department of Veterans Affairs. (2008). VA healthcare eligib ility and enrollment. Retrieved March 2, 2008 from h ttp://www.va.gov/healtheligibility/ Department of Veterans Affairs. (2007). Facts about the department of Veterans affairs. Retrieved December 12, 2007 from http://www1.va.gov/opa/fact/docs/vafacts.doc Dillm an, D.A. (2000) Mail and Internet Surveys the Tailored Design Method New York: John Wiley & Sons, Inc. Evenson, K.R., Rosamond, W.D., & Luepker, R.V. (1998). Predictors of outpatient cardiac rehabilitation utilization: The Minnesota Heart Survey Registry. Journal of Cardiopulmonary Rehabilitation and Prevention 18(3), 192-198. Finkelstein, E.A., Fiebelkorn, I.C., & Wa ng, G. (2003). National medical spending attributable to overweight and obes ity: How much and whos paying? Health Affairs; W3; 219-226. Finucane, F.M., Gaffney, L., Hatunic, M., Burns, N., & Nolan, J.J. (2007). Attendance at an Irish Diabetes Dietetic Outpatient Clinic. Diabetes Research and Clinical Practice 77, 335-336. George, A. & Rubin, G. (2003). Non-attendance in general practice: a systematic review and its implications for access to primary health care. Family Practice 20(2), 178184.

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97 Gucciardi, E., DeMelo, M., Offenheim, A., Grace S.L., & Stewart, D.E. (2007). Patient factors associated with attrition from a self-management education programme. Journal of Evaluation in Clinical Practice 13, 913-919. Hagan, N.A., Botti, M.A., & Watts, R.J. (2007). Financial, family, and social factors impacting on cardiac reha bilitation attendance. Heart & Lung 36(2), 105-113. Hardy, K.J., O'Brien, S.V., & Furlong, N.J. ( 2001). Information given to patients before appointments and its effect on non-attendance rate. British Medical Journal, 323, 1298-1299. Hershberger, P.J., Robertson, K.B., & Markert, R.J. (1999). Personality and appointmentkeeping adherence in cardiac rehabilitation. Journal of Cardiopulmonary Rehabilitation, 19, 106-111. Humphreys, L. Hunter A.G.W., Zimak, A ., OBrien, A., Korneluk, Y., & Cappelli, M. (2000). Why patients do not attend for their appointments at a genetics clinic. Journal of Medical Genetics, 37(10), 810-815. Hussain-Gambles, M., Neal, R.D., Dempsey, O., Lawlor, D.A., & Hodgson, J. (2004). Missed appointments in primary care: quest ionnaire and focus group study of health professionals. British Journal of General Practice 54, 108-113. Izard, T. (2005). Managing the habitual no-show patient. [Electronic version]. Family Practice Management, (February), 65-66. Killaspy, H., Banerjee, S., King, M., & Lloyd, M. (2000). Prospective controlled study of psychiatric out-patient non-attendance. British Journal of Psychiatry 176,160-154 Krueger, R. & Casey, M.A. (2000) Focus Groups: A Practical Guide for Applied Research 3rd edition. Thousand Oaks: Sage Publications, Inc.

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98 Lacy, N.L., Paulman, A., Reuter, M.D., & Lovejoy, B. (2004). Why we don't come: Patient perceptions on no-shows. Annals of Family Medicine 2(6), 541-545. Little, B., Cannon, C., Whitson, B., & Jarolim, D.R. (1991). The Failed Appointment. Journal of the Oklahoma St ate Medical Association 84(9), 455-458. Martin, C., Perfect, T., & Mantle, G. (2005). Non-attendance in primary care: The views of patients and practices on its causes, impact, and solutions. Family Practice Advance Access, 22 638-643. McKinley, M.J., Goodman-Block, J., Lesser, M.L., & Salbe, A.D. (1994) Improved body weight status as a result of nutrition interv ention in adult, HIV-positive outpatients. Journal of the American Dietetic Association 94(9), 1014-1017. Mokdad, A.I., Ford, E.S., & Bowman, B.A. (2003), et al. Prevalence of obesity, diabetes, and obesity-related health risk factors. Journal of the American Medical Association, 89:76-79. Mugavero, M.J., Lin, H., Allison, J.J., Willig, J.H., Chang, P., Marler, M., Raper, J.L., Schumacher, J.E., Pisu, M., & Saag, M.S. (2007). Failure to establish HIV care: characterizing the no show phenomenon. Clinical Infectious Diseases 45, 127130. Murdock, A., Rodgers, C., Lindsay, H., & Tham, T.C.K. (2002). Why do patients not keep their appointments? Prospective study in a gastroenterol ogy outpatient clinic. Journal of the Royal Society of Medicine 95, 284-286. Neal, R.D., Lawlor, D.A., Allgar, V., Colle dge, M., Ali, S., Hassey, A., Portz, C., & Wilson, A. (2001). Missed appointments in general practice: retrospective data analysis from four practices. British Journal of General Practice, 51, 830-832.

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99 Nowicki, E., Billington, C., Levine, A., Hoove r, H., Must, A., & Naumova, E. (2003). Overweight, obesity, and a ssociated disease burden in the Veterans affairs ambulatory care population. Military Medicine, 168 252-256. Ogden. C.L., Carroll, M.D., Curtin, L.R., McDowell, M.A., Tabak, C.J., & Flegal, K.M. Prevalence of overweight and obesity in the United States, 1999 (2006). Journal of the American Medical Association, 295(13):1549-55. Procidano, M., & Heller, K. ( 1983). Measures of perceived social support from friends and from family: Three validation studies. American Journal of Community Psychology, 11, 1. Pavlovich, W.D., Waters, H., Weller, W., & Bass, E.B. (2004) Systemic review of literature on the cost-effectiveness of nutrition services. Journal of the American Dietetic Association, 104(2), 226-232. Ramm, C., Robinson, S., & Sharpe, N. (2001). Factors determining non-attendance at a cardiac rehabilitation programme fo llowing myocardial infarction. New Zealand Medical Journal, 114, 227-229. Reiber, G.E., Koepsell, T.D., Maynard, C., H aas, L.B., & Boyko, E.J. (2004) Diabetes in nonVeterans, Veterans, and Veterans rece iving Department of Veterans Affairs health care. Diabetes Care, 27 Suppl 2:B3-9. Rhee, M., Ziemer, D., Slocum, W., Culler, S., Cook, C., El Kebbi., Gallina, D., & Phillips, L. (2003). Keeping appointments improves glycemic control. Diabetes, 52 Supplement A209. Rohland, B.M. (2004). Appointment attendance predicts level of gl ycaemic control in people with diabetes. Evidence-based Healthcare 8, 195-196.

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100 Rose, M.S. & Chung, M.K. (2003). On with the show. Medical Group Management Association, 3(1), 54-57. Sharp, D.J. & Hamilton, W. (2001). Non-attend ance at general practices and outpatient clinics. British Medical Journal, 323, 1081-1082. Sheils, J.F., Rubin, R., & Stapleton, D.C. ( 1999). The estimated coasts and savings of medical nutrition therapy: the Medicare population. Journal of the American Dietetic Association 99(4), 428-435. Spikmans, F.J.M., Brug, J., Doven, M.M.B., Kruizenga, H.M., Hofsteenge, G.H., & van Bokhorst-van der Schueren, M.A.E. (2003) Why do diabetic patients no attend appointments with their dietitian? Journal of Human Nutrition and Dietetics 16, 151-158. Strauss, A. and Corbin, J. (1990). Basics of Qualitative Research: Grounded Theory procedures and Techniques. Thousand Oaks: Sage Publications U.S. Department of Health and Human Servic es. The Surgeon Genera ls call to action to prevent and decrease overweight and obes ity. [Rockville, MD]: U.S. Department of Health and Human Services, Public Health Service, Office of the Surgeon General; [2001]. Available from: US GPO, Washington. Vaux, A., Phillips, J., Holly, L., Thomson, B ., Williams, D., & Stew art, D. (1986). The social support appraisals (SS-A) Scal e: Studies of reliability and validity. American Journal of Community Psychology 14, 195. Waller, J. & Hodgkin, P. (2000). Defaulters in general practice: who are they and what can be done about them? Family Practice, 17, 252-253.

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101 Weinger, K., McMurrich, S.J., Yi, J.P., Li n, S., & Rodriquez, M. (2005). Psychological characteristics of frequent short-notice can cellers of diabetes medical and education appointments. Diabetes Care, 28, 1791-1793. Ziemer, D.C., Ferguson, S.Y., Kieltyka, R. L., & Slocum, W. (1998). Barriers to appointment keeping behavior in a munici pal hospital diabetes clinic [Abstract]. Abstract book: 58th Scientific Sessions: Saturday June 13 Tuesday June 16, 1998. Published by the American Diab etes Association 47(1S), p. 144a.

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102 APPENDICES

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103 Appendix A, Historical Appointment Trends Figure 2. Appointment trends for am bulatory care nutrition clinics FY2007 0 50 100 150 200 250 300 350Oct No v De c Ja n Feb M ar ch Ap ril M ay J une Ju ly Aug Se pt total seen no show cancellation Figure 3. Appointment trends for am bulatory care nutrition clinics FY2006 0 50 100 150 200 250 300 350 400 450Oct Nov Dec Jan Feb Mar April May Jun Jul Aug Sep Total seen no show cancellation

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104 Appendix B, Pre-letter (Phone Interview) In Reply Refer To: 673/120B Date Inside address (of recipient) Dear I am writing to ask for your help with an important research project being conducted by the James A. Haley Veterans Hospital. This study is part of an important effort to improve the nutrition services we offer Vete rans. Results from study will help us understand what affects appointment attendance and will give us information that may be used to improve nutrition programs at the VA. You have been selected because you were sc heduled for a nutrition appointment in the last month and we would like to hear your f eedback and opinions. To participate in the study we are asking you to take part in a telephone interview. We estimate it will take about 20 minutes to complete the interview. This survey is voluntary and deciding not to participate will not a ffect your care in any way. However, you can help us very much be taking a few minutes to share your experiences and opinions about nutrition appointments at the VA. If for some reason you prefer not to be interv iewed, please let us know by calling (813)972-2000 x6336 and leaving a message stating that your preference not to participate. We will allow one week from the time this letter is sent. If we do not receive a message, we will attempt to call you for a telephone interview. This research is considered to be minimal risk. That means that the risks associated with this study are the same as what you face every day. There are no known additional risks to those who take part in this study. We dont know if you will get any benefits by taking part in this study. We will not pay you for the time you volunteer while being in this study. Your answers are completely confidential. We will only publish a summary of what we have learned from everyone we interview. No individual Veterans answers will be identified. When you return your complete d questionnaire, your name will be deleted from the mailing list and never connect ed to your answers in any way. DEPARTMENT OF VETERANS AFFAIRS James A. Haley Veterans Hospital 13000 Bruce B. Downs Blvd Tampa, FL 33612

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105 Appendix B (Continued) If you have any questions, concerns, or comm ents about this study, I would be happy to talk with you. Please call me at (813) 972-2000 x6336, or you can write to: James A. Haley Veterans Hospital Claire Bell, 120B 13000 Bruce B. Downs Blvd Tampa, FL 33612 Thank you very much for helping with this important study. Sincerely, Claire F. Bell

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106 Appendix C, Telephone Recruitm ent and Interview Script Introduction Hello, m ay I please speak to [name] If the person is at home: Hello, I am Claire Bell from the Tampa VA calling about a research project I am conducting as a student at the Un iversity of South Florida. (Skip to explanation.) If the person is not at home and speaking to a family member? Hello, I am Claire Bell from the Tampa VA calling about a research project I am conducting as a student at the Un iversity of South Florida. When would be a good time to reach him? Could I get a number where I could reach him? If the person is not at home and an answering machine is reached: Hello, I am Claire Bell from the Tampa VA calling about a research project I am conducting as a student at the University of South Florida. I would like to ask you a few questions regarding a recent nutrition appointment you were scheduled for. If you could please call me back, my number is 813-972-2000 x6336. Explanation You (or name of person) have been selected to participate in a ver y important project I am working on to learn more about opini ons about nutrition appointments at the VA. May I tell you a littl e more about this?

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107 Appendix C (Continued) If not thank them and tell them that they can call you if they change their mind. If yes, continue. What I would like to do is interview you, and ask you a few questions about your experiences, thoughts, and opinions related to nutrition appointments at the VA. Your personal information will be kept in strict confidence. Participation is voluntary. Declining participa tion will not impact your care at the VA. If you decide to participate, I will need to get your verbal permission to interview you by phone. Also, with your permission I would like to record the call. If you prefer not to have the call recorded we do not have to. Do mind if I record? I anticipate this interview should take about 20 minutes. Just a few more things I would also like to let you know that this research is cons idered to be minimal risk. That means that the risks associated with this study are the same as what you face every day. There are no known additional risks to those who take part in this study. We dont know if you will get any benefits by taking part in this study. We will not pay you for the time you volunteer while being in this study. Would you like to go ahead w ith the interview? If not, thank them and give them a number to call if they change their mind. (813)972-2000 x6336 If yes, continue.

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108 Appendix C (Continued) We want to find out more about what makes it easy and what makes it difficult to attend nutrition appointment. We are interested in your ideas to change or improve the VA nutrition programs, and plan to use what we l earn from this research to improve nutrition programs at the VA. Thinking about VA appointments in general What do you think makes it easy for a person to attend appointments? What do you think makes it hard fo r people to attend appointments? Now, thinking more specifically about your recently scheduled nutrition appointment, Tell me about how the appointment was scheduled (probing for patient requesting thei r own appointment versus provider recommending it) Did your provider discuss the r eason for the appointment? If so, what was the reason? Did the provider encourage you to attend? How long did you wait to have your nutrition appointment? How did you feel about the length of time you had to wait? (probe if needed: Was this an appropriate am ount of time to wait? If no-show or cancellation: Can you describe what you expected the nutrition appointment to be like? If they attended : How did your experience compare with your expectations? Please tell me about your reasons fo r coming to (or missing) the nutrition appointment? Probes: What other reasons? What else?

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109 Appendix C (Continued) If attended : What could have prev ented you from attending? If missed : What could have made it easier to attend? How did you feel about having to see the di etitian? Can you tell me a little more about why you felt that way? Who influenced your decision to attend? Wh at did they do that affected whether or not you went? How did your spouse/partner/family affect your decision to attend the appointment? How did your health care team (doctor, nurse, pharmacist, physician assistant) influence your decision? Did you have to make special travel a rrangements to come to the appointment? What would make it more appeal ing to learn about nutrition? In an ideal situation, what can be changed to make it easier for people to attend nutrition appointments? o Do you have a time of day that you prefer for appointments? o What about weekends versus weekdays? And just a few last questions to wrap up here. Can you please tell me how many people are in your household? What is your employment status? How many years of education have you completed? Do you have any other healthcare insurance besides the VA? Do you attend non-VA nutrition appointments using other insurance?

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110 Appendix D, Survey Variables Demographic Variables Age Attendance History (in the past month, and ever) BMI (height/weight) Disability status (VA and Non-VA) Employment status Family size/number in household Gender Income Insurance Marital status Years of Education Completed Cognitive factors Attitude towards appointment How referred/scheduled (on patients request or on the recommendation of the provider) Memory (forgetting) Outcome efficacy Perceived health Perceived importance of the appointment Perceived trust of VA vs. civilian health care Satisfaction with dietetic care Understanding of the scheduling system

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111 Appendix D, Survey Variables Structural Competing priorities Traveling/out of town Work Family care Cost Feeling unwell Parking: time, difficulty Perceived difficulty attending scheduling because VA is too busy Reminder letter Reminder call Scheduling: ability to request conveni ent time; use of scheduling system Travel Time Transportation difficulty Wait time Weather Who referred (doctor, pharmacist, nurse, etc) Way finding (difficulty finding location of appointment) Social Perceived encouragement from health care professional Perceived encouragement from family and friends

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112 Appendix E, Survey Cover Letter In Reply Refer To: 673/120B Date Inside address (of recipient) Dear I am writing to ask for your help with an important research project being conducted by the James A. Haley Veterans Hospital. This study is part of an important effort to improve the nutrition services we offer Veterans. Results from this survey will help us understand what affects appointment attendance and will give us information that may be used to improve nutrition programs at the VA. You have been selected because you were sc heduled for a nutrition appointment in the last month and we would like to hear your f eedback and opinions. To participate in the study we are asking that you complete one mail su rvey and return it in the enclosed prepaid envelope. We estimate it will take you about 20 minutes to fill out the survey. This survey is voluntary and deciding not to participate will not a ffect your care in any way. However, you can help us very much by taking a few minutes to share your experiences and opinions about nutrition appointments at the VA. If for some reason you prefer not to respond, please le t us know by returning the blank questionnaire in the enclosed pre-paid envelope. This research is considered to be minimal risk. That means that the risks associated with this study are the same as what you face every day. There are no known additional risks to those who take part in this study. We dont know if you will get any benefits by taking part in this study. We will not pay you for the time you volunteer while being in this study. By completing this survey, and returning it, you are c onsenting to partic ipate in the study. Your answers are completely confidential. We will only publish a summary of what we have learned from everyone we survey. No individual Veterans answers will be identified. When you return your completed questionnaire, your name will be deleted DEPARTMENT OF VETERANS AFFAIRS James A. Haley Veterans Hospital 13000 Bruce B. Downs Blvd Tampa, FL 33612

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113 Appendix E (Continued) from the mailing list and never connected to your answers in any way. If you have any questions or comments about this study, I would be happy to talk with you. Please call me at (813) 972-2000 x6336, or you can write to: James A. Haley Veterans Hospital Claire Bell, 120B 13000 Bruce B. Downs Blvd Tampa, FL 33612 Thank you very much for helping with this important study. Sincerely, Claire F. Bell

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114 Appendix F, Survey Reminder Post Card Date Last week a questionnaire seeking your opinion about nutrition appointments at the VA was mailed to you. If you have already completed and returned the ques tionnaire to us, please accept our sincere thanks. If not, please do so today. We are especially grat eful for your help because it is only by asking Veterans like you to share your experiences and opinions that we can understand why people attend nutrition appointments at what we can do to improve nutrition programs. If you did not receive a questionnaire, or if it wa s misplaced, please call us at 813-972 -2000 x6336 and we will get another one in the mail to you today. Claire F. Bell James A. Haley Veterans Hospital 13000 Bruce B. Downs Ave, 120B Tampa, FL 33613 DEPARTMENT OF VETERANS AFFAIRS James A. Haley Veterans Hospital 13000 Bruce B. Downs Blvd Claire F. Bell, N&FS, 120B Tampa, FL 33612 Insert recipient address

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115 Appendix G, Third Mailing Cover Letter In Reply Refer To: 673/120B Date Inside address (of recipient) Dear A few weeks ago a questionnaire seeking your opinion about nutri tion appointments at the James A. Haley hospital was mailed to you. This questionnaire is part of an important research study that is being done to improve the nutrition services we offer Veterans. If you have already completed and returned the questionnaire to us, please accept our sincere thanks. If not, please do so today. A new copy of the questionnaire is enclosed for your convenience. We are especially gr ateful for help because it is only by asking people like you to share your experiences th at we can understand your opinions about nutrition appointments. You were selected because you were scheduled for a nutrition appointment in the last month and we would like to hear your feedba ck and opinions. To participate in the study we are asking that you complete one mail survey and return it in the enclosed pre-paid envelope. We estimate it will take you a bout 20 minutes to fill out the survey. This survey is voluntary and deciding not to participate will not a ffect your care in any way. However, you can help us very much be taking a few minutes to share your experiences and opinions about nutrition appointments at the VA. If for some reason you prefer not to respond, please le t us know by returning the blank questionnaire in the enclosed pre-paid envelope. This research is considered to be minimal risk. That means that the risks associated with this study are the same as what you face every day. There are no known additional risks to those who take part in this study. We dont know if you will get any benefits by taking part in this study. We will not pay you for the time you volunteer while being in this study. DEPARTMENT OF VETERANS AFFAIRS James A. Haley Veterans Hospital 13000 Bruce B. Downs Blvd Tampa, FL 33612

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116 Appendix G (Continued) Your answers are completely confidential. We will only publish a summary of what we have learned from everyone we survey. No individual Veterans answers will be identified. When you return your complete d questionnaire, your name will be deleted from the mailing list and never connect ed to your answers in any way. If you have any questions or comments about this study, I would be happy to talk with you. Please call me at (813) 972-2000 x6336, or you can write to: James A. Haley Veterans Hospital Claire Bell, 120B 13000 Bruce B. Downs Blvd Tampa, FL 33612 Thank you very much for helping with this important study, Sincerely, Claire F. Bell

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117 Appendix H, Survey Start here The following questions ask about a nutrition appoi ntment you were scheduled for in the past month. Think back to the date of your most recently scheduled appointment and answer the following questions. (Pleas e circle your answer.) Yes No Dont Know 1. Have you attended a nutrition appointment in the past month? 1 2 3 2. Did you receive a reminder phone call for a nutrition appointment in the past month? 1 2 3 3. Did you receive a reminder letter/postcard for a nutrition appointment in the past month? 1 2 3 4. Were you able to request an appointment time that was convenient to you? 1 2 3 5. At the time of the appointment, were you employed full time? 1 2 3 6. At the time of the appointment, were you traveling or on vacation? 1 2 3 7. At the time of the appointment, did bad weather interfere with keeping the appointment? 1 2 3 8. At the time of your appointment, did you have transportation difficulty? 1 2 3 9. At the time of your appointment, were you attending to family needs (such as caring for a loved one or attending a funeral)? 1 2 3 10. At the time of your appointment, did you feel well enough to attend? 1 2 3 11. At the time of the appointments, did the cost of the appointment keep you from attending (for example the cost of gas, or co-pays)? 1 2 3 12. Did you forget to attend your last nutrition appointment? 1 2 3

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117 Appendix H (Continued) 13. From the time it was scheduled, how many days did you have to wait for your appointment? In other words, how many days lapsed between the day you scheduled it and the day you had your appointment?) 0 days 1-14 days 15-30 days 31-45 days More than 45 I have never attended a nutrition appointment Not sure/does not apply 14. At the time of your last scheduled nutrition appointment, how long did it take you to travel from where you live to the James A. Haley VA? 0-30 minutes 31-60 minutes 61-90 minutes 91-120 minutes (1 -2 hours) More than 2 hours 15. At the time of your last scheduled nutrition appointment, how long did it take you to park? 0-30 minutes 31-60 minutes more than 60 minutes Does not apply 16. Besides the past month, have you ever attended a nutrition appointment? Yes No Not sure 17. Besides the VA, do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare? Yes No Dont know / Not sure 18. How satisfied were you with the care you received at the last nutrition appointment you had at the VA? Completely satisfied Somewhat satisfied Neither satisfied nor dissatisfied Somewhat dissatisfied Completely dissatisfied Does not apply, you did not attend 19. Compared to what you expected the appointment to be like, would you say the nutrition appointment: Greatly exceeded your expectations Somewhat exceeded your expectations Met your expectations Fell somewhat below your expectations Fell a great deal below your expectations Does not apply, you did not attend

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118 Appendix H (Continued) 20. Who referred you to the nutrition appointment? My doctor/primary care provider Nurse Pharmacist Psychologist/Mental Health Professional I requested the appointment myself None of the above 21. Which of the following best describes how you were referred to the nutrition appointment? I requested the appointment on my own My doctor told me to go My doctor recommended I go My doctor and I decided together I was automatically scheduled for the appointment Other The following questions ask about a nutrition appointment you were scheduled for in the past month. Think back to your most r ecently scheduled nutrition appointment as you answer the following questions. (Please circle your answer.) Strongly Agree Some what agree Neither agree nor disagree Somewhat Disagree Strongly Disagree Don't know 22. My family and friends encouraged me to attend the last nutrition appointment I was scheduled for at the VA. 1 2 3 4 5 6 23. A health professional encouraged me to attend the last nutrition appointment I was scheduled for at the VA. 1 2 3 4 5 6 24. I looked forward to attending the nutrition appointment. 1 2 3 4 5 6 25. Attending the nutrition appointment was important to my health. 1 2 3 4 5 6

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119 Appendix H (Continued) The following questions address your general opinion about nutrition appointments. To what extent do you agree or disagree with th e following statements? (Please circle your answer.) Strongly Agree Somewhat agree Neither agree nor disagree Somewhat Disagree Strongly Disagree Not Sure 26. When someone misses a nutrition appointment, there are fewer appointment openings for other Veterans. 1 2 3 4 5 6 27. When someone misses a nutrition appointment, the dietitian has free time. 1 2 3 4 5 6 28. I believe a dietitian is a knowledgeable source of health information. 1 2 3 4 5 6

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120 Appendix H (Continued) The following questions address your general opinion about the James A. Haley VA. To what extent do you agree or disagree with th e following statements? (Please circle your answer.) Strongly Agree Somewh at agree Neither agree nor disagree Somewhat Disagree Strongly Disagree Not sure 29. I trust James A. Haley more than civilian healthcare. 1 2 3 4 5 6 30. James A. Haley better understands my healthcare needs than civilian healthcare. 1 2 3 4 5 6 31. I have had difficulty attending an appointment because of trouble with parking. 1 2 3 4 5 6 32. I have had difficulty attending an appointment because the VA is too busy. 1 2 3 4 5 6 33. The scheduling system is easy to use. 1 2 3 4 5 6 34. I have had difficulty attending an appointment because I could not find the location of the appointment. 1 2 3 4 5 6

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121 Appendix H (Continued) 35. Which of the following best describes your current employment status? Check all that apply. Employed for wages full time Employed for wages part time Self-employed Out of work, more than 1 year Out of work, less than 1 year A homemaker A student Retired Unable to work 36. How would you describe your health at the time of your last nutrition appointment? Excellent Very good Good Fair Poor 37. Are you currently receiving service connected disability ? (VA disability) Yes No 38. Are you currently receiving non-VA disability? Yes No 39. What is your marital status? Married Divorced Widowed Separated Single Unmarried, living together 40. Including yourself, how many people live in the same house with you? 1 (you only) 2 3 4 or more 41. How old are you? ____Years 42. What is your gender? Male Female Please write in your height and weight. 43. Height: _____feet _____ inches 44. Weight: ________ pounds 45. What day of the week would you most prefer to have a nutrition appointment? Monday-Friday (weekdays) Saturday (weekend) No preference 46. What time of day would you most prefer to have a nutrition appointment? Morning Afternoon Evening

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Appendix H (Continued) 47. What is the highest grade or year of school you have completed? Never attended school or only kindergarten grades 1-8 grades 9-11 high school graduate or GED college 1-3 years (some college or technical school) college 4 years or more (college graduate) 48. Which of the following categories best describes your yearly household income? $9999 or less $10,000-14,999 $15,000-19,999 $20,000-24,999 $25,000-34,999 $35,000-49,999 $50,000-74,999 $75,000+ Prefer not to answer Please note, in the mailed vers ion, the survey was kept to 5 pages, questions 21 and 48 did not split onto separate pages. Some of th e original formatting to the survey was lost to due compliance with thesis submission guidelines. Thank you for completing the survey. Please make a dditional comments on the back of this page. Return the survey in the enclosed pr e-paid/pre addressed return envelop.

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123 Appendix I, Summary of Missingness variable complete responses missing responses not sure/don't know/does not apply Reported attendance 345 0 4 Reminder call 329 3 17 Reminder letter 330 3 16 Convenient time 329 2 18 Employment at time of Appointment 347 2 0 Travel 342 4 3 Weather 344 3 2 Transportation 347 1 1 Family care 345 1 3 Feeling well 334 4 11 Cost 343 2 4 Forget 341 3 5 Wait days 328 10 11 Travel time 336 13 0 Parking time 294 13 42 Previously attended nutrition Appointment 334 11 4

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124 Insurance 335 9 5 Satisfaction 304 10 35 Expectations 304 10 35 Who referred 337 12 0 How referred 338 11 0 Family support 320 13 16 Provider support 330 13 6 Looked forward to appointment 330 13 6 Importance 333 11 5 Understanding of impact1 326 9 14 Understanding of impact2 277 9 63 RD knowledge 339 8 2 Trust 334 10 5 VA versus Civilian 332 11 6 Parking 334 13 2 VA too busy 331 11 7 Scheduling System 331 13 5

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125 Appendix I (Continued) Way finding 336 11 2 Employment 336 13 0 Perceived health 330 19 0 Disability 331 19 0 Non VA disability 325 24 0 Marital Status 332 16 0 Household size 332 17 0 Age 334 15 0 Gender 333 16 0 Height 328 21 0 Weight 327 22 0 Preferred Day 325 24 0 Preferred Time 325 23 0 Education 333 16 0 Income 269 24 55 BMI 324 25 0

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126 Appendix J, Demographic Vari ables Descriptive Summary Survey Respondent Demographic Characteristics Variable Attended Did not attend Total Mean Range Mean Range Mean Range Age 59.97 26-79 58.6 30-76 59.7 26-79 BMI 30.8 14.6-55.528.95 17.6-51.730.4 14.6-55.5 Gender Male 253 76 329 n % n % n % Household Size 1 2 3 >4 55 21.8 119 47.2 38 15.1 40 15.8 17 22.4 30 39.5 17 22.4 12 15.8 72 22 149 45.4 55 16.8 52 15.9 Attendance History Never attended Previously attended 77 29.2 181 69.6 37 50 37 50 113 33.7 2198 65.1 Insurance Status Private insurance VA only 141 53.8 117 44.7 28 37.3 45 60 169 50.1 162 48

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127 VA Disability Yes No 131 52 121 48 34 45.3 41 54.7 165 50.5 162 49.5 Non VA Disability Yes No 53 21.5 194 78.5 17 21.3 57 77 70 20.3 251 72.8 Marital Status n(%) Married Divorced Widowed Separated Single Living together 148 58.7 41 16.3 11 4.4 13 5.2 33 12.7 8 2.8 41 53.9 19 25 1 1.3 4 5.3 9 10.5 3 3.9 189 57.9 60 18.3 12 3.7 17 5.2 40 12.2 10 3.0 Health Status Excellent Very Good Good Fair Poor 9 3.5 50 19.7 109 42.9 63 24.8 23 9.1 4 5.5 6 8.2 25 32.9 28 38.4 11 15.1 13 4.0 56 17.1 133 40.7 91 27.6 34 10.4

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128 Years of Education grades 1-8 grades 9-11 high school/GED college 1-3 years college or more 4 1.6 9 3.5 75 29.4 109 42.7 58 21.9 2 2.7 5 6.8 23 31.1 34 45.9 10 13.5 6 1.8 14 4.3 98 29.8 143 43.5 68 20.7 Employment Status Employed full time Employed part time Self-employed Out of work, >1 yr Out of work, < 1yr Homemaker Student Retired Unable to work 42 16.5 11 4.3 20 7.8 21 8.2 19 7.5 1 4 2 .8 92 36.1 47 18.4 9 11.4 2 3.8 2 2.5 10 12.7 3 3.8 0 0 1 1.3 25 31.3 25 31.3 51 15.4 13 3.9 22 6.6 31 9.3 22 6.6 1 .3 3 .9 117 35.2 72 21.7

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129 Income $9999 or less $10,000-14,999 $15,000-19,999 $20,000-24,999 $25,000-34,999 $35,000-49,999 $50,000-74,999 $75,000+ Prefer not to answer 32 13.0 34 13.8 20 8.1 24 9.7 34 13.8 28 11.3 16 6.5 20 8.1 39 15.8 13 18.3 14 19.7 2 2.8 10 14.1 2 2.8 8 11.3 4 5.6 3 4.2 15 21.1 45 14.2 48 15.1 22 6.9 34 10.7 36 11.3 36 11.3 20 6.3 23 7.2 54 17.0