567813 research-article2015
CNU0010.1177/1474515114567813European Journal of Cardiovascular Nursing 0(0)Vasaroangrong et al.
EUROPEAN SOCIETY OF CARDIOLOGY ®
Original Article
Factors influencing prehospital delay time among patients with peripheral arterial occlusive disease
European Journal of Cardiovascular Nursing 2016, Vol. 15(4) 285–293 © The European Society of Cardiology 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1474515114567813 cnu.sagepub.com
Tidarat Vasaroangrong1, Orapan Thosingha2, Barbara Riegel3, Chanean Ruangsetakit4 and Chukiat Viwatwongkasem5
Abstract Background: Only one-third of patients with peripheral arterial occlusive disease (PAOD) seek medical care after perceiving the symptoms of PAOD, and most PAOD patients only visit the physician when they develop ulceration and gangrene. Delay can result in lower extremity amputation and death within three years. The aim of this study was to predict prehospital delay time from sociodemographic characteristics and clinical characteristics, social support, knowledge about PAOD, depression and fear, and treatment-seeking behaviors among patients with PAOD. Method and results: Data were collected in three university hospitals in Bangkok, Thailand. A sample of 212 patients with PAOD who were newly diagnosed or diagnosed within the preceding four months was recruited into the study. Questionnaires and interviewing were used to collect data. Stepwise multiple regression analysis was performed to identify the factors influencing prehospital delay time. Significant determinants of prolonged prehospital delay time were male gender, low monthly income (less than 10,000 Thai baht or 213 Euros), high level of perceived social support, and several treatment seeking behaviors. Depression, high level of fear, and self-pay of medical expenses were associated with short prehospital delay time. Overall, the model explained 41.0% of the variance in prehospital delay time. Conclusion: Clinicians need to develop intervention programs and national campaigns to increase knowledge about PAOD among patients in these high risk groups. Keywords Peripheral arterial occlusive disease, prehospital delay time, treatment seeking behaviors, depression, social support, fear Date received: 2 September 2014; revised: 16 December 2014; accepted: 17 December 2014
Introduction Peripheral arterial occlusive disease (PAOD) is a manifestation of systemic atherosclerosis. PAOD is related to increased risk of coronary heart disease, stroke, carotid stenosis, and increased risk of death from ischemic events.1–3 The disease results from interference in blood circulation caused by gradual formation of atherothrombosis, which leads to arterial stenosis.4 The severity of its symptoms depends on the degree of stenosis and occlusion of peripheral blood vessels, which affects the amounts of oxygen and nutrients delivered to tissues at distal parts of the limbs.4 If the stenosis is narrow, pain at rest usually occurs, followed by ischemic ulcers and tissue gangrene, eventually leading to extended death of soft tissues and muscles of the extremities.
PAOD affects populations worldwide, especially in Europe. Previous studies have found that asymptomatic PAOD, i.e. having an ankle brachial index (ABI) less than 0.90, affects one-fifth of the population, while symptomatic 1Faculty
of Graduate Studies, Mahidol University, Thailand of Nursing, Mahidol University, Thailand 3School of Nursing, University of Pennsylvania, USA 4Faculty of Medicine, Mahidol University, Thailand 5Faculty of Public Health, Mahidol University, Thailand 2Faculty
Corresponding author: Orapan Thosingha, 2 Prannok Rd., Siriraj Sub District, Bangkok-noi, Bangkok, 10700, Thailand. Email: [email protected]
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
286
European Journal of Cardiovascular Nursing 15(4)
PAOD affects 10% of the total population.5,6 Interestingly, most PAOD patients wait to visit a physician until they have ulceration and gangrene.7 In Thailand, where this study was conducted, the number of patients with PAOD is increasing. A study conducted by Mutirangura and colleagues8 revealed that the prevalence of PAOD was 102 per 100,000 population. The majority of patients who come to a tertiary care hospital generally have a limb-threatening condition and require intensive vascular management, including revascularization and/or amputation.8 This figure also confirms that the majority of patients with PAOD access medical care only after they have reached a catastrophic stage. It is worth noting that in general patients who received primary amputation had a mortality rate 2.6 times greater than that of patients who received revascularization.8 Prehospital delay time is crucial and related to morbidity and mortality among patients with acute illnesses9,10 and chronic illnesses.11–13 In patients with PAOD, prehospital delay time is defined as the time from onset of PAOD symptoms to the time patients decide to seek treatment at the hospital. However, research on the exact time of prehospital delay among patients with PAOD is rare. In Thailand, there is a descriptive study conducted by Sawangphong14 which reported that the majority of patients started to seek treatment only after they had developed gangrene and ulcers. This study draws on a conceptual framework inspired by self-regulation theory,15 the crucial factors related to prehospital delay time can be categorized into four domains. The first domain is internal and environmental stimuli, which trigger the process of labeling and interpreting the PAOD symptoms. The response to such stimuli depends on sociodemographic characteristics (gender, age, educational level, income, medical expense), clinical characteristics, and the social support of patients. The second factor influencing delay is symptoms; the response to symptoms is based on patients’ knowledge about PAOD. The third factor is patients’ emotions in response to PAOD symptoms including depression and fear. The final factor is the behavior that patients with PAOD use to deal with the severity of their symptoms in terms of treatment-seeking behaviors (Figure 1). Research regarding factors related to prehospital delay time in patients with PAOD in Thailand has received little attention. The one study carried out by Sawangphong14 exploring factors related to the first time diagnosis in patients with PAOD did not analyze the association between prehospital delay time and sociodemographic characteristics, clinical characteristics, social support, knowledge about PAOD, emotions, and treatment-seeking behaviors of patients. Accordingly, the purpose of this study was to fill this gap in the literature on factors influencing prehospital delay in Thai patients with PAOD. The knowledge from this study can give direction to healthcare
Cognitive representation
Knowledge of PAOD Emotional representation -Depression -Fear
Coping and appraisal Treatment seeking behavior
Outcomes Prehospital delay time
Internal and environmental stimuli -Sociodemographic characteristics -Clinical characteristics -Social Support
Figure 1. Conceptual framework of this study. PAOD: peripheral arterial occlusive disease.
providers in developing strategies to prevent prehospital delay among patients with PAOD.
Methods Patients and setting This cross-sectional study was conducted between December 2011–July 2012. Patients with PAOD who received treatment at an outpatient department of three university hospitals, in Bangkok, Thailand i.e. Siriraj Hospital, Ramathibodi Hospital, and Phramongkutklao Hospital, were invited to participate in the study if they met the inclusion criteria: new diagnosis of PAOD or diagnosis within the prior four months, cognitively intact, and ability to communicate in spoken and written Thai. Patients with acute PAOD and patients with arterial occlusion from other causes, including traumatic vascular disorders, inflammation, or embolism were excluded. There were 215 individuals who participated in this study. However, three patients were subsequently excluded because they had an ambiguous health history. Therefore, data collected from 212 participants (143 from Siriraj Hospital, 25 from Ramathibodi Hospital, and 44 from Phramongkutklao Hospital) were analyzed. Data collection was conducted after the research was approved by the Institutional Review Boards (IRBs) of each setting. The investigation was conducted in a manner that complies with the principles outlined in the Declaration of Helsinki. The study detail was explained to each patient and a written informed consent was obtained before data collection began.
Measurements The data regarding the patients’ demographic and medical characteristics were collected by the demographic and medical record form. The following instruments were used
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
287
Vasaroangrong et al. in data collection: (a) Multidimensional Scale of Perceived Social Support (MSPSS); (b) knowledge about PAOD questionnaire; (c) Hospital Anxiety and Depression Scale; (d) a visual analog fear scale; (e) treatment seeking behavior questionnaire; and (f) sequence of time interview form. All instruments administered by interviewing and all data were collected by the principal investigator. The MSPSS was developed by Zimet and colleagues.16 It is a 12-item self-reported measure used to assess perceived social support. The items were scored on a sevenpoint rating scale with response options ranging from 1 (very strongly disagree) to 7 (very strongly agree). Boonyamalik17 translated the MSPSS scale from English into Thai and used it to measure perceived social support in Thai adolescents attending schools. Content validity was evaluated by five experts in the field of PAOD. The content validity index (CVI) was 1.0. The internal consistency reliability was 0.80 for overall support and 0.85, 0.75, and 0.85 for the subscales of support from partner, family, and friends, respectively. The knowledge about PAOD questionnaire was developed by the first author based on an extensive literature review. It contained three dimensions consisting of knowledge about PAOD symptoms (seven items), PAOD risk factors (five items), and the effects of PAOD (four items), in total comprising 16 items. Content validity was evaluated by five experts in the field of PAOD. The CVI was 0.87. PAOD questionnaire is a dichotomous scale, the response of this questionnaire is “Yes” or “No” so that the Kuder-Richardson Coefficient of reliability or KR-20 was employed to test internal consistency reliability of this questionnaire. The result showed that the reliability of PAOD questionnaire was 0.73. The Hospital Anxiety and Depression Scale (HADS) was developed by Zigmond and Snaith.18 Nilchaikovit and colleagues19 translated this instrument into Thai language and administered it to cancer patients. A domain of depression (seven items) was used to assess depression in this study. Content validity was evaluated and approved by PAOD experts; the CVI of the HADS was 1.0. The internal consistency reliability of this subscale was 0.90. A visual analog fear scale was developed by the researcher from related literature. This scale consisted of five items (i.e. uncontrollable pain, loss of function, loss of independence, loss of leg, and loss of life ), each of which was associated with a 10 cm visual analog scale,20 with an end point of 0 for “no fear” and 10 for “extreme fear.” The patients were asked “How much fear do you have about …?” and made a mark on the line representing their feelings. Content validity was evaluated and approved by PAOD experts; the CVI was 0.95. Treatment-seeking behavior was elicited using a standardized interview conducted by the researcher. The first question elicited the patient’s perception about symptoms related to PAOD. The second question asked for data on how they manage their symptoms. After that, data regarding the frequency and effectiveness of each treatment
seeking behavior were elicited. Content analysis was employed for data analysis. Then, the amounts of treatment seeking behaviors were calculated to form a continuous variable. The sequence of time was assessed to allow computation of prehospital delay time. The interview sequence was designed by the researcher to capture data regarding healthcare services used by the patients. Data regarding which setting was visited and the duration from onset of the PAOD symptoms prior to utilization of healthcare services in each setting were captured in these interviews, all of which were done by the primary researcher. Prehospital delay time was calculated as the time from onset of the PAOD symptoms until the day that patients came to a healthcare setting to receive PAOD treatment.
Data analysis Descriptive statistics were used to describe the study sample. The test of between-subjects effects was performed to explore the association between the settings and prehospital delay time. The test revealed that there were no differences in the prehospital delay time of patients from each hospital (F=0.36, p=0.52). Stepwise multiple regression analysis was performed to identify the factors influencing prehospital delay time, i.e. gender, age, education, income, medical expense, comorbidity, social support, knowledge about PAOD, depression, fear, and treatment seeking behaviors. Since data regarding prehospital delay time was severely skewed to the right, log transformation was used before multiple regression was employed. Dummy variables were used for the variables of income and medical expense to prevent violation of multiple regression assumptions. An alpha level of 0.05 was accepted. All analyses were performed with SPSS 17.0 for Windows.
Results The participants had an average age of 66.03 years (standard deviation (SD)=12.56 years) with ages ranging from 40–89 years. Most participants were men with a low level of education and a low income. Most did not seek medical care until their disease had reached Stage IV with ulceration or gangrene. The vast majority of patients had comorbid conditions, and the most commonly found comorbidities were diabetes mellitus and hypertension (Table 1). Table 2 illustrates the mean scores on the measures of social support, knowledge of PAOD, depression, and fear. In general, it can be seen that social support was high, but knowledge about PAOD was low. Furthermore, fear was high, but depression was low. Close to half of the patients (42.5%) applied wound dressings themselves as the first attempt at self-care to relieve their symptoms, followed by applying a balm (17.5%) and waiting to see if the symptoms would go away (12.7%). Many patients (46.7%) tried all three approaches.
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
288
European Journal of Cardiovascular Nursing 15(4)
Table 1. Demographics and characteristics among patients with peripheral arterial occlusive disease (PAOD) (n=212). Variables
%
Demographics Age (years) 80 (late elderly)
Gender Male Female
59.9 40.1
Educational level None Elementary school Secondary school Diploma or technical Bachelor or above
2.8 51.9 22.2 7.5 15.6
31.2 23.1 32.5 13.2
Monthly household income: Thai baht (Euros) Less than 5000 ( 445)
34.9 24.1 22.1 7.1 11.8
Source of medical expense Self payment Reimbursement Universal coverage Social security
7.6 37.7 46.2 8.5
Medical history Fontaine’s stage of disease (n=212) Stage I asymptomatic Stage II intermittent claudication Stage III rest pain Stage IV ulceration or gangrene
1.4 29.3 6.6 62.7
Location of occlusion Tibio-peroneal artery Femoro-popliteal artery Aorto-iliac artery Ilio-femoral artery
39.1 32.1 14.0 10.7
Comorbidities Diabetes mellitus Hypertension Dyslipidemia Coronary artery disease End stage renal disease Cerebrovascular disease Arthritis Chronic obstructive pulmonary disease Congestive heart failure Spinal stenosis None comorbidities
65.1 60.4 31.1 20.8 10.8 9.9 7.5 6.1 2.8 2.4 9.0
The interesting inter-correlation among independent variables that should be addressed was depression (Table 3). Depression had significantly negative correlation with male gender (r= −0.38, p=0.000), education (r= −0.45, p=0.000), and social support (r= −0.21, p=0.002). While it showed positive correlation with age (r=0.28, p=0.000), income less than 10,000 baht/month (10,000 Thai baht or approximately 213 Euros) (r=0.45, p=0.002), and knowledge (r=0.15, p=0.013).
Prehospital delay time The duration of prehospital delay time varied from 1−910 days, but most delayed less than 30 days (Table 2).
Factors influencing prehospital delay time among patients with PAOD In the final step of stepwise multiple regression modeling of prehospital delay time, male gender, low monthly income, high level of perceived social support, and several treatment seeking behaviors were found to be associated with prolonged prehospital delay time. On the contrary, depression, high level of fear, and self-pay of medical expenses were associated with short prehospital delay time. The overall model explained 41% of the variance in prehospital delay time (F=4.88, p
CNU0010.1177/1474515114567813European Journal of Cardiovascular Nursing 0(0)Vasaroangrong et al.
EUROPEAN SOCIETY OF CARDIOLOGY ®
Original Article
Factors influencing prehospital delay time among patients with peripheral arterial occlusive disease
European Journal of Cardiovascular Nursing 2016, Vol. 15(4) 285–293 © The European Society of Cardiology 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1474515114567813 cnu.sagepub.com
Tidarat Vasaroangrong1, Orapan Thosingha2, Barbara Riegel3, Chanean Ruangsetakit4 and Chukiat Viwatwongkasem5
Abstract Background: Only one-third of patients with peripheral arterial occlusive disease (PAOD) seek medical care after perceiving the symptoms of PAOD, and most PAOD patients only visit the physician when they develop ulceration and gangrene. Delay can result in lower extremity amputation and death within three years. The aim of this study was to predict prehospital delay time from sociodemographic characteristics and clinical characteristics, social support, knowledge about PAOD, depression and fear, and treatment-seeking behaviors among patients with PAOD. Method and results: Data were collected in three university hospitals in Bangkok, Thailand. A sample of 212 patients with PAOD who were newly diagnosed or diagnosed within the preceding four months was recruited into the study. Questionnaires and interviewing were used to collect data. Stepwise multiple regression analysis was performed to identify the factors influencing prehospital delay time. Significant determinants of prolonged prehospital delay time were male gender, low monthly income (less than 10,000 Thai baht or 213 Euros), high level of perceived social support, and several treatment seeking behaviors. Depression, high level of fear, and self-pay of medical expenses were associated with short prehospital delay time. Overall, the model explained 41.0% of the variance in prehospital delay time. Conclusion: Clinicians need to develop intervention programs and national campaigns to increase knowledge about PAOD among patients in these high risk groups. Keywords Peripheral arterial occlusive disease, prehospital delay time, treatment seeking behaviors, depression, social support, fear Date received: 2 September 2014; revised: 16 December 2014; accepted: 17 December 2014
Introduction Peripheral arterial occlusive disease (PAOD) is a manifestation of systemic atherosclerosis. PAOD is related to increased risk of coronary heart disease, stroke, carotid stenosis, and increased risk of death from ischemic events.1–3 The disease results from interference in blood circulation caused by gradual formation of atherothrombosis, which leads to arterial stenosis.4 The severity of its symptoms depends on the degree of stenosis and occlusion of peripheral blood vessels, which affects the amounts of oxygen and nutrients delivered to tissues at distal parts of the limbs.4 If the stenosis is narrow, pain at rest usually occurs, followed by ischemic ulcers and tissue gangrene, eventually leading to extended death of soft tissues and muscles of the extremities.
PAOD affects populations worldwide, especially in Europe. Previous studies have found that asymptomatic PAOD, i.e. having an ankle brachial index (ABI) less than 0.90, affects one-fifth of the population, while symptomatic 1Faculty
of Graduate Studies, Mahidol University, Thailand of Nursing, Mahidol University, Thailand 3School of Nursing, University of Pennsylvania, USA 4Faculty of Medicine, Mahidol University, Thailand 5Faculty of Public Health, Mahidol University, Thailand 2Faculty
Corresponding author: Orapan Thosingha, 2 Prannok Rd., Siriraj Sub District, Bangkok-noi, Bangkok, 10700, Thailand. Email: [email protected]
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
286
European Journal of Cardiovascular Nursing 15(4)
PAOD affects 10% of the total population.5,6 Interestingly, most PAOD patients wait to visit a physician until they have ulceration and gangrene.7 In Thailand, where this study was conducted, the number of patients with PAOD is increasing. A study conducted by Mutirangura and colleagues8 revealed that the prevalence of PAOD was 102 per 100,000 population. The majority of patients who come to a tertiary care hospital generally have a limb-threatening condition and require intensive vascular management, including revascularization and/or amputation.8 This figure also confirms that the majority of patients with PAOD access medical care only after they have reached a catastrophic stage. It is worth noting that in general patients who received primary amputation had a mortality rate 2.6 times greater than that of patients who received revascularization.8 Prehospital delay time is crucial and related to morbidity and mortality among patients with acute illnesses9,10 and chronic illnesses.11–13 In patients with PAOD, prehospital delay time is defined as the time from onset of PAOD symptoms to the time patients decide to seek treatment at the hospital. However, research on the exact time of prehospital delay among patients with PAOD is rare. In Thailand, there is a descriptive study conducted by Sawangphong14 which reported that the majority of patients started to seek treatment only after they had developed gangrene and ulcers. This study draws on a conceptual framework inspired by self-regulation theory,15 the crucial factors related to prehospital delay time can be categorized into four domains. The first domain is internal and environmental stimuli, which trigger the process of labeling and interpreting the PAOD symptoms. The response to such stimuli depends on sociodemographic characteristics (gender, age, educational level, income, medical expense), clinical characteristics, and the social support of patients. The second factor influencing delay is symptoms; the response to symptoms is based on patients’ knowledge about PAOD. The third factor is patients’ emotions in response to PAOD symptoms including depression and fear. The final factor is the behavior that patients with PAOD use to deal with the severity of their symptoms in terms of treatment-seeking behaviors (Figure 1). Research regarding factors related to prehospital delay time in patients with PAOD in Thailand has received little attention. The one study carried out by Sawangphong14 exploring factors related to the first time diagnosis in patients with PAOD did not analyze the association between prehospital delay time and sociodemographic characteristics, clinical characteristics, social support, knowledge about PAOD, emotions, and treatment-seeking behaviors of patients. Accordingly, the purpose of this study was to fill this gap in the literature on factors influencing prehospital delay in Thai patients with PAOD. The knowledge from this study can give direction to healthcare
Cognitive representation
Knowledge of PAOD Emotional representation -Depression -Fear
Coping and appraisal Treatment seeking behavior
Outcomes Prehospital delay time
Internal and environmental stimuli -Sociodemographic characteristics -Clinical characteristics -Social Support
Figure 1. Conceptual framework of this study. PAOD: peripheral arterial occlusive disease.
providers in developing strategies to prevent prehospital delay among patients with PAOD.
Methods Patients and setting This cross-sectional study was conducted between December 2011–July 2012. Patients with PAOD who received treatment at an outpatient department of three university hospitals, in Bangkok, Thailand i.e. Siriraj Hospital, Ramathibodi Hospital, and Phramongkutklao Hospital, were invited to participate in the study if they met the inclusion criteria: new diagnosis of PAOD or diagnosis within the prior four months, cognitively intact, and ability to communicate in spoken and written Thai. Patients with acute PAOD and patients with arterial occlusion from other causes, including traumatic vascular disorders, inflammation, or embolism were excluded. There were 215 individuals who participated in this study. However, three patients were subsequently excluded because they had an ambiguous health history. Therefore, data collected from 212 participants (143 from Siriraj Hospital, 25 from Ramathibodi Hospital, and 44 from Phramongkutklao Hospital) were analyzed. Data collection was conducted after the research was approved by the Institutional Review Boards (IRBs) of each setting. The investigation was conducted in a manner that complies with the principles outlined in the Declaration of Helsinki. The study detail was explained to each patient and a written informed consent was obtained before data collection began.
Measurements The data regarding the patients’ demographic and medical characteristics were collected by the demographic and medical record form. The following instruments were used
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
287
Vasaroangrong et al. in data collection: (a) Multidimensional Scale of Perceived Social Support (MSPSS); (b) knowledge about PAOD questionnaire; (c) Hospital Anxiety and Depression Scale; (d) a visual analog fear scale; (e) treatment seeking behavior questionnaire; and (f) sequence of time interview form. All instruments administered by interviewing and all data were collected by the principal investigator. The MSPSS was developed by Zimet and colleagues.16 It is a 12-item self-reported measure used to assess perceived social support. The items were scored on a sevenpoint rating scale with response options ranging from 1 (very strongly disagree) to 7 (very strongly agree). Boonyamalik17 translated the MSPSS scale from English into Thai and used it to measure perceived social support in Thai adolescents attending schools. Content validity was evaluated by five experts in the field of PAOD. The content validity index (CVI) was 1.0. The internal consistency reliability was 0.80 for overall support and 0.85, 0.75, and 0.85 for the subscales of support from partner, family, and friends, respectively. The knowledge about PAOD questionnaire was developed by the first author based on an extensive literature review. It contained three dimensions consisting of knowledge about PAOD symptoms (seven items), PAOD risk factors (five items), and the effects of PAOD (four items), in total comprising 16 items. Content validity was evaluated by five experts in the field of PAOD. The CVI was 0.87. PAOD questionnaire is a dichotomous scale, the response of this questionnaire is “Yes” or “No” so that the Kuder-Richardson Coefficient of reliability or KR-20 was employed to test internal consistency reliability of this questionnaire. The result showed that the reliability of PAOD questionnaire was 0.73. The Hospital Anxiety and Depression Scale (HADS) was developed by Zigmond and Snaith.18 Nilchaikovit and colleagues19 translated this instrument into Thai language and administered it to cancer patients. A domain of depression (seven items) was used to assess depression in this study. Content validity was evaluated and approved by PAOD experts; the CVI of the HADS was 1.0. The internal consistency reliability of this subscale was 0.90. A visual analog fear scale was developed by the researcher from related literature. This scale consisted of five items (i.e. uncontrollable pain, loss of function, loss of independence, loss of leg, and loss of life ), each of which was associated with a 10 cm visual analog scale,20 with an end point of 0 for “no fear” and 10 for “extreme fear.” The patients were asked “How much fear do you have about …?” and made a mark on the line representing their feelings. Content validity was evaluated and approved by PAOD experts; the CVI was 0.95. Treatment-seeking behavior was elicited using a standardized interview conducted by the researcher. The first question elicited the patient’s perception about symptoms related to PAOD. The second question asked for data on how they manage their symptoms. After that, data regarding the frequency and effectiveness of each treatment
seeking behavior were elicited. Content analysis was employed for data analysis. Then, the amounts of treatment seeking behaviors were calculated to form a continuous variable. The sequence of time was assessed to allow computation of prehospital delay time. The interview sequence was designed by the researcher to capture data regarding healthcare services used by the patients. Data regarding which setting was visited and the duration from onset of the PAOD symptoms prior to utilization of healthcare services in each setting were captured in these interviews, all of which were done by the primary researcher. Prehospital delay time was calculated as the time from onset of the PAOD symptoms until the day that patients came to a healthcare setting to receive PAOD treatment.
Data analysis Descriptive statistics were used to describe the study sample. The test of between-subjects effects was performed to explore the association between the settings and prehospital delay time. The test revealed that there were no differences in the prehospital delay time of patients from each hospital (F=0.36, p=0.52). Stepwise multiple regression analysis was performed to identify the factors influencing prehospital delay time, i.e. gender, age, education, income, medical expense, comorbidity, social support, knowledge about PAOD, depression, fear, and treatment seeking behaviors. Since data regarding prehospital delay time was severely skewed to the right, log transformation was used before multiple regression was employed. Dummy variables were used for the variables of income and medical expense to prevent violation of multiple regression assumptions. An alpha level of 0.05 was accepted. All analyses were performed with SPSS 17.0 for Windows.
Results The participants had an average age of 66.03 years (standard deviation (SD)=12.56 years) with ages ranging from 40–89 years. Most participants were men with a low level of education and a low income. Most did not seek medical care until their disease had reached Stage IV with ulceration or gangrene. The vast majority of patients had comorbid conditions, and the most commonly found comorbidities were diabetes mellitus and hypertension (Table 1). Table 2 illustrates the mean scores on the measures of social support, knowledge of PAOD, depression, and fear. In general, it can be seen that social support was high, but knowledge about PAOD was low. Furthermore, fear was high, but depression was low. Close to half of the patients (42.5%) applied wound dressings themselves as the first attempt at self-care to relieve their symptoms, followed by applying a balm (17.5%) and waiting to see if the symptoms would go away (12.7%). Many patients (46.7%) tried all three approaches.
Downloaded from cnu.sagepub.com at TEXAS SOUTHERN UNIVERSITY on May 26, 2016
288
European Journal of Cardiovascular Nursing 15(4)
Table 1. Demographics and characteristics among patients with peripheral arterial occlusive disease (PAOD) (n=212). Variables
%
Demographics Age (years) 80 (late elderly)
Gender Male Female
59.9 40.1
Educational level None Elementary school Secondary school Diploma or technical Bachelor or above
2.8 51.9 22.2 7.5 15.6
31.2 23.1 32.5 13.2
Monthly household income: Thai baht (Euros) Less than 5000 ( 445)
34.9 24.1 22.1 7.1 11.8
Source of medical expense Self payment Reimbursement Universal coverage Social security
7.6 37.7 46.2 8.5
Medical history Fontaine’s stage of disease (n=212) Stage I asymptomatic Stage II intermittent claudication Stage III rest pain Stage IV ulceration or gangrene
1.4 29.3 6.6 62.7
Location of occlusion Tibio-peroneal artery Femoro-popliteal artery Aorto-iliac artery Ilio-femoral artery
39.1 32.1 14.0 10.7
Comorbidities Diabetes mellitus Hypertension Dyslipidemia Coronary artery disease End stage renal disease Cerebrovascular disease Arthritis Chronic obstructive pulmonary disease Congestive heart failure Spinal stenosis None comorbidities
65.1 60.4 31.1 20.8 10.8 9.9 7.5 6.1 2.8 2.4 9.0
The interesting inter-correlation among independent variables that should be addressed was depression (Table 3). Depression had significantly negative correlation with male gender (r= −0.38, p=0.000), education (r= −0.45, p=0.000), and social support (r= −0.21, p=0.002). While it showed positive correlation with age (r=0.28, p=0.000), income less than 10,000 baht/month (10,000 Thai baht or approximately 213 Euros) (r=0.45, p=0.002), and knowledge (r=0.15, p=0.013).
Prehospital delay time The duration of prehospital delay time varied from 1−910 days, but most delayed less than 30 days (Table 2).
Factors influencing prehospital delay time among patients with PAOD In the final step of stepwise multiple regression modeling of prehospital delay time, male gender, low monthly income, high level of perceived social support, and several treatment seeking behaviors were found to be associated with prolonged prehospital delay time. On the contrary, depression, high level of fear, and self-pay of medical expenses were associated with short prehospital delay time. The overall model explained 41% of the variance in prehospital delay time (F=4.88, p
