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| ORIGINAL ARTICLE |
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| Year : 2020 | Volume
: 4
| Issue : 3 | Page : 80-84 |
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Program planning in education and light exercise training for atrial fibrillation patients: A feasibility study
Connor Tripp1, Zachary Force1, Nichelle L Huber1, J Paul Mounsey2, Aditi Naniwadekar3, Rajasekhar Nekkanti3, Samuel F Sears4
1 Department of Psychology, East Carolina University, Greenville, North Carolina, USA
2 Division of Cardiovascular Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
3 Department of Cardiovascular Sciences, East Carolina University, Greenville, North Carolina, USA
4 Department of Psychology; Department of Cardiovascular Sciences, East Carolina University, Greenville, North Carolina, USA
| Date of Submission | 11-Jun-2020 |
| Date of Acceptance | 10-Aug-2020 |
| Date of Web Publication | 29-Sep-2020 |
Correspondence Address:
Ms. Connor Tripp
104 Rawl Building, Department of Psychology, East Carolina University, Greenville 27834, North Carolina
USA
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/hm.hm_25_20
Background: Contemporary management of patients with atrial fibrillation (AF) indicates the need for educational and self-care programs to address lifestyle factors. Aims: This study examined the clinical need and interest in programming for risk factor modification in AF patients residing in a mostly rural area. Methods: Participants with AF (n = 86) were recruited during university-based cardiac electrophysiology appointments and asked to complete a 10-min survey battery assessing a range of risk factors spanning physical activity, knowledge, ability, interest, and engagement, as well as psychologic function. Results: AF risk factor reports indicated broad potential need for AF programming with an average CHADS-VASC of 3.8, with approximately 67% reporting low physical activity, and 38% significant anxiety. Related to self-care topics, education on physical activity was the highest-rated program, but weight-loss programming was rated as the most likely to attend. Distance to the clinic was the most often cited barrier, 50% of sample. Conclusions: AF patients demonstrated a need and view educational programming in the realm of physical activity and weight-loss as desirable. Increased research is needed to determine format and duration of treatment deemed efficacious and able to overcome specific barriers such as distance to care.
Keywords: Atrial fibrillation, patient education, physical activity, psychological distress, self-care
How to cite this article:
Tripp C, Force Z, Huber NL, Mounsey J P, Naniwadekar A, Nekkanti R, Sears SF. Program planning in education and light exercise training for atrial fibrillation patients: A feasibility study. Heart Mind 2020;4:80-4 |
How to cite this URL:
Tripp C, Force Z, Huber NL, Mounsey J P, Naniwadekar A, Nekkanti R, Sears SF. Program planning in education and light exercise training for atrial fibrillation patients: A feasibility study. Heart Mind [serial online] 2020 [cited 2023 Mar 27];4:80-4. Available from: http://www.heartmindjournal.org/text.asp?2020/4/3/80/296563 |
| Introduction | |  |
Atrial fibrillation (AF) is the most common type of arrhythmia, affecting both men and women, associated with a five times greater risk of stroke.[1] Symptoms of AF can include weakness, dyspnea, chest pain, palpitations, and neurologic symptoms.[2] Stress and negative health behaviors are associated with increased symptom experience and burden in patients with AF.[3],[4],[5],[6]
The management of AF can involve a host of patient behaviors that can modify the causes and consequences of the condition. For example, AF patients are asked to adhere to multiple health behaviors such as medication adherence, dietary change, weight management, decreased alcohol intake, and increased physical activity. Specialized management of AF including education on treatment options, risk factors, details of how medication/treatment works, and when to report to a hospital, resulted in significantly less all-cause and cardiovascular mortality as compared to usual care.[7] However, the best means of providing lifestyle change assistance to the full care of AF patients has not been established. For example, it is not known whether AF patients would engage fully in aspects of care such as classes about AF and its treatments, stress and AF, exercise and AF, or cardiac rehabilitation for AF. The acceptability and effectiveness of such a resource intensive program remains to be established across settings.
The current study aims to assess AF patient readiness to participate in educational and light exercise programs. The study will also describe AF patient readiness to participate in educational and light exercise programs, as well as patient's current physical and psychological function.
| Methods | | |
Participants were recruited from a university-based cardiac electrophysiology clinic in the Southeastern United States during regularly scheduled appointments. Participants were approached about the study by their attending cardiologist. After expressing interest in the project, participants were introduced to research coordinators and asked to complete a 10-min survey battery assessing physical activity, knowledge, ability, interest, and engagement, as well as psychologic function.
Measures
Duke activity status index (DASI) is a 12-item, self-report measure that assesses a patient's functional capacity, used to provide a rough estimate of a patient's peak oxygen uptake. Respondents were asked to respond “yes” or “no” as to their ability to engage in various physical activity.[8] The scale is significantly correlated with peak oxygen uptake with a spearman correlation coefficient of 0.80.
Depression anxiety and stress scale-21 (DASS-21) is a twenty-one item, self-report measure of psychological function. The scale assesses general psychological distress (α = 0.93) and is comprised of three subscales: depression (α = 0.88), anxiety (α = 0.82), and stress (α = 0.90).[9] The items are on a 4-point Likert Scale ranging from 0 (did not apply to me at all) to 4 (applied to me very much or most of the time).
Godin Leisure-Time Exercise Questionnaire is a two-item, self-report measure of a patient's current physical activity engagement. Respondents were asked how often they engage in strenuous, moderate and mild exercise during an average week for more than 15 min during their free time.[10] Respondents were also asked to rate the frequency they exercise long enough to work up a sweat; answer choices include often, sometimes, and never/rarely.
The researcher-developed interest and barriers questionnaire were developed by the authors specifically for this study, as a six-item measure used to describe patient interest and barriers to participation in educational and light exercise programs at East Carolina Heart Institute. Respondents were provided with nine options of education (e.g., symptom management and weight loss) or exercise (e.g., walking and yoga) groups for individuals with AF. They were instructed to “select all that apply,” if any, to indicate those that they believe are helpful, are interested in attending if offered free of cost, and would not consider helpful for improving cardiac health. Respondents were also asked if they had ever considered participating in a group to improve their health and if physician recommendation would influence their participation. Finally, respondents are asked to indicate barriers toward participation including no limitations, not interested, transportation, distance, time, health, limited mobility, and understanding material.
After surveys were completed, a medical record review was conducted to confirm AF diagnosis and demographic information including age, ethnicity, body mass index (BMI), AF type, and AF symptom status. Information on medical comorbidities was also gathered for the calculation of CHA2 DS2-VASc stroke risk scores.
| Results | | |
The sample consisted of AF patients (n = 86, 52% male, 69% Caucasian, 31% African American) with a mean age of 67 years (standard deviation [SD] = 10, range = 38–87). Average BMI was 32.8 (SD = 7.5), suggesting that this sample, on average, fell within the CDC's classification for obesity.[11] More specifically, only 10 patients fell within the normal range, while n = 76 were considered overweight/obese.
Regarding AF type, medical record review indicated 1% permanent, 53% paroxysmal, and 46% persistent, with 63% experiencing symptomatic AF. Medical record review also provided information on the prevalence of multiple disease states for the purpose of calculating CHA2 DS2-VASc stroke risk scores [Table 1]. The mean CHA2 DS2-VASc stroke risk score was 3.8 (SD = 1.85), with a minimum score of 0 and a maximum score of 9. Obstructive sleep apnea was present in less than half of the samples (43%), as well as alcohol use (23%).
Physical activity
Scores on the DASI suggested low functional capacity in this sample, with a mean functional capacity of 7 METS (SD = 2.2) and Peak V02 of 24.8 (SD = 7.7); however, it is notable that this only represents an estimate and may in part reflect the age of the sample. According to the patient responses on the Godin Leisure-Time Exercise Questionnaire, when asked how many times per week patients engage in meaningful exercise (i.e., “long enough to work up a sweat”), 27 (32%) patients reported often, 29 (34%) reported sometimes, and 28 (33%) reported never/barely.
Psychological functioning
DASS-21 subscales scores of stress, anxiety, and depression are categorized into groups indicating normal, mild, moderate, severe, and extremely severe symptomology. DASS-21 scores from this sample are presented in [Table 2] and suggest that a significant number of patients in this sample reported distress in the moderate, severe, or extremely severe range, indicating a possible need for further psychological assessment and treatment. Most notably, 38% of patients in this sample reported anxious symptoms in the moderate, severe, or extremely severe range.
Interests and barriers to program participation
Patient responses to the interest and barriers questionnaire are described in [Table 3]. Overall, the patients reported that educational programs for physical activity (65%), weight loss (58%), medication management (51%), and sleep (48%) would be helpful for individuals with AF; they reported that walking group (50%) and stretching (Yoga) group (34%) may also be helpful for individuals with AF.
Fifty participants (58%) indicated that they had already considered participating in an educational or exercise group for improving their cardiac health. However, when patients were asked if they would attend these programs if offered free of cost, numbers were slightly lower (e.g., sleep [29%], medication management [26%], weight loss [50%], physical activity [44%], walking group [47%], and stretching [Yoga] group [27%]). Major barriers to participation included distance (50%), time (29%), and transportation (20%). More than half of the patients (70%) indicated that physician recommendation would influence their decision to participate in an educational or light exercise program to improve their cardiac health. Anecdotally, patients frequently responded to questions about barriers stating if these opportunities were offered in their communities, they would be more likely to attend. Many of the patients travelled long distances from surrounding rural areas for medical care.
| Discussion | | |
The current study examined AF patient needs and preferences to participate in educational and self-care programs related to AF management in a predominantly rural area. AF risk factors were highly prevalent in this sample with an average CHADS-VASC of 3.8, low levels of physical activity, and high levels of significant anxiety, 67% and 38%, respectively. Related to self-care topics, education on physical activity was the highest-rated program, but weight-loss programming was rated as the most likely to attend. Multiple barriers to care were identified including distance to the clinic (50%), time (29%), and transportation (20%).
AF is increasingly being considered a lifestyle condition[12] and the efficacy of catheter ablation may also be significantly affected by risk factor modification.[13] The predominant work in this area has been completed by Australian researchers using large community samples. The generalizability and acceptability of similar approaches in the US and in rural settings are unknown. This study sought to examine the feasibility in our locale to determine how to best increase patient engagement and success. The nature of risk factor modification and behavioral change tend to denote a significant mid-to-long-term commitment to professional support and engagement to increase the probability of success across physical activity, dietary changes, and self-care programs.
Our findings underline the importance of both weight loss and physical activity approaches for AF patients. Behavioral approaches to weight loss have called for multi-modality programming with the expected results of 5%–10% weight loss.[14] Recent research has underlined a “small changes” approach that may improve long-term maintenance.[15] Moderate physical activity has been associated with improvements in exercise capacity, quality of life (QOL), blood pressure, and heart rate for patients with AF.[16],[17],[18],[19] Interestingly, yoga has been associated with significant improvements in heart rate, blood pressure, and oxygen consumption, as well as reductions in symptom experience, symptom burden, and improvements in QOL for patients with AF.[20],[21] To the best of our knowledge, no previous research in rural AF patients has examined the patient interest or willingness to engage in yoga or light exercise training.
This study provides direction for program planning to assist with risk factor modification for AF patients residing in more rural areas. This cross-sectional study established the presence of multiple AF risk factors and psychological distress in AF patients. The average CHADSVASC scores and low rates of physical activity underscored the need for programming. The high rates of psychological stress (38%) are consistent with previous literature.[22] While the Southeast US represents a large portion of the stroke belt likely indicating a need for intervention,[23] barriers to initiation of and participation in such programs exist. Many factors that contribute to higher risk are also those that would limit ability to participate (i.e., health-care access and socioeconomic status).[24] For example, this Southeastern medical center provides healthcare for 29 counties, many patients travel long distances for medical care. This represents issues of time, cost, transportation, and distance highlighted in this study. In addition, lifestyle interventions are resource intensive and compensation for providers is often limited.
The current study also has some limitations to consider. This sample was drawn from a university-based cardiology clinic in a predominantly rural area. These patients rated programs through the lens of barriers that they face such as transportation and distance to care. These findings may not generalize to all settings, but the data serve as a starting point to program planning for many settings. The emergence of AF risk factor care may present more challenges to rural AF patients. The survey that we used was not previously tested and no reliability data are available. However, there was sufficient psychometric validation of the other measures in the study. Finally, the relationship between ratings of programs and actual participation is unknown, but future studies examining feasibility and follow-up of programming would be valuable.
Implications for practice
AF risk factor programming represents an important next step for the care of AF patients. The current study suggests that common behavioral risk factors exist in a rural sample of AF patients. Low levels of physical activity and high levels of anxiety exist. Educational programs for AF patients were rated and physical activity was the highest-rated program, but weight-loss programming was rated as the most likely to attend. Barriers to care included distance to the clinic and time and transportation challenges. Increased research is needed to determined format and duration of efficacious treatments to reduce AF risk factors and improve patient outcomes.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Yaghi S, Kamel H. Stratifying stroke risk in atrial fibrillation: Beyond clinical risk scores. Stroke 2017;48:2665-70.  |
| 2. | Andrade JG, Macle L, Nattel S, Verma A, Cairns J. Contemporary atrial fibrillation management: A comparison of the current AHA/ACC/HRS, CCS, and ESC guidelines. Can J Cardiol 2017;33:965-76. |
| 3. | Freeman JV, Reynolds K, Fang M, Udaltsova N, Steimle A, Pomernacki NK, et al. Digoxin and risk of death in adults with atrial fibrillation: The ATRIA-CVRN study. Circ Arrhythm Electrophysiol 2015;8:49-58. |
| 4. | Gehi AK, Sears S, Goli N, Walker TJ, Chung E, Schwartz J, et al. Psychopathology and symptoms of atrial fibrillation: Implications for therapy. J Cardiovasc Electrophysiol 2012;23:473-8. |
| 5. | Thompson TS, Barksdale DJ, Sears SF, Mounsey JP, Pursell I, Gehi AK. The effect of anxiety and depression on symptoms attributed to atrial fibrillation. Pacing Clin Electrophysiol 2014;37:439-46. |
| 6. | Westcott SK, Beach LY, Matsushita F, Albert CM, Chatterjee N, Wong J, et al. Relationship between psychosocial stressors and atrial fibrillation in women >45 Years of Age. Am J Cardiol 2018;122:1684-7. |
| 7. | Hendriks JML, Tieleman RG, Vrijhoef HJM, Wijtvliet P, Gallagher C, Prins MH, et al. Integrated specialized atrial fibrillation clinics reduce all-cause mortality: Post hoc analysis of a randomized clinical trial. Europace 2019;21:1785-92. |
| 8. | Hlatky MA, Boineau RE, Higginbotham MB, Lee KL, Mark DB, Califf RM, et al. A brief self-administered questionnaire to determine functional capacity (the Duke Activity Status Index). Am J Cardiol 1989;64:651-4. |
| 9. | Henry JD, Crawford JR. The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. Br J Clin Psychol 2005;44:227-39. |
| 10. | Godin G, Shephard RJ. Godin leisure-time exercise questionnaire. Med Sci Sports Exerc 1997;29:36-8. |
| 11. | |
| 12. | Voskoboinik A, Wong G, Lee G, Nalliah C, Hawson J, Prabhu S, et al. Moderate alcohol consumption is associated with atrial electrical and structural changes: Insights from high-density left atrial electroanatomic mapping. Heart Rhythm 2019;16:251-9. |
| 13. | Pathak RK, Fahed J, Santangeli P, Hyman MC, Liang JJ, Kubala M, et al. Long-term outcome of catheter ablation for treatment of bundle branch re-entrant tachycardia. JACC Clin Electrophysiol 2018;4:331-8. |
| 14. | Aldaas OM, Lupercio F, Han FT, Hoffmayer KS, Krummen D, Ho G, et al. Meta-analysis of effect of modest (≥10%) weight loss in management of overweight and obese patients with atrial fibrillation. Am J Cardiol 2019;124:1568-74. |
| 15. | Lutes LD, Damschroder LJ, Masheb R, Kim HM, Gillon L, Holleman RG, et al. Behavioral treatment for veterans with obesity: 24-month weight outcomes from the ASPIRE-VA Small changes randomized trial. J Gen Intern Med 2017;32:40-7. |
| 16. | Mertens DJ, Kavanagh T. Exercise training for patients with chronic atrial fibrillation. J Cardiopulm Rehabil 1996;16:193-6. |
| 17. | Plisiene J, Blumberg A, Haager G, Knackstedt C, Latsch J, Norra C, et al. Moderate physical exercise: A simplified approach for ventricular rate control in older patients with atrial fibrillation. Clin Res Cardiol 2008;97:820-6. |
| 18. | Osbak PS, Mourier M, Henriksen JH, Kofoed KF, Jensen GB. Effect of physical exercise training on muscle strength and body composition, and their association with functional capacity and quality of life in patients with atrial fibrillation: A randomized controlled trial. J Rehabil Med 2012;44:975-9. |
| 19. | Malmo V, Nes BM, Amundsen BH, Tjonna AE, Stoylen A, Rossvoll O, et al. Aerobic interval training reduces the burden of atrial fibrillation in the short term: A randomized trial. Circulation 2016;133:466-73. |
| 20. | Krishna BH, Pravati P, Pal G, et al. Effect of yoga therapy on heart rate, blood pressure and cardiac autonomic function in heart failure. J Clin Diagn Res 2014;8:14-6. |
| 21. | Abdul-Aziz AA, Altawil M, Lyon A, MacEachern M, Richardson CR, Rubenfire M, et al. Lifestyle therapy for the management of atrial fibrillation. Am J Cardiol 2018;121:1112-7. |
| 22. | McCabe PJ, Barnason SA. Illness perceptions, coping strategies, and symptoms contribute to psychological distress in patients with recurrent symptomatic atrial fibrillation. J Cardiovasc Nurs 2012;27:431-44. |
| 23. | Tchwenko SN. The burden of cardiovascular disease in North Carolina. Technical Report; 2012. |
| 24. | Howard G, Howard VJ, Katholi C, Oli MK, Huston S. Decline in US stroke mortality: An analysis of temporal patterns by sex, race, and geographic region. Stroke 2001;32:2213-20. |
[Table 1], [Table 2], [Table 3]
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