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Asthma severity in children and the quality of life of their parents
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Applied Nursing Research 25 (2012) 131 – 137 www.elsevier.com/locate/apnr
Original Articles
Asthma severity in children and the quality of life of their parents Noelle S. Cerdan, RN, CPNPa , Patricia T. Alpert, DrPH, APNb,⁎, Sheniz Moonie, PhDc , Dianne Cyrkiel, MSN, APNd , Shona Rue, MSN, CPNPd a Oshiro Pediatrics, Las Vegas, NV 89119-6183, USA School of Nursing, University of Nevada, Box 453018, Las Vegas, NV 8154-3018, USA c School of Community Health Sciences, University of Nevada, Box 453063 Las Vegas, NV 89154-3063, USA d School of Nursing, University of Nevada, Box 453018, Las Vegas, NV 8154-3018, USA Received 31 March 2010; revised 3 January 2011; accepted 17 January 2011 b
Abstract
This study examines the effect of asthma severity of children aged 7–17 years and sociodemographic characteristics on the caregiver's quality of life. For parents of asthmatic children, there was a negative correlation between overall asthma severity and quality-of-life score. Measuring parental quality of life enables the development of effective asthma programs. Published by Elsevier Inc.
1. Introduction
2. Background
Quality of life (QOL) can be described as general satisfaction with everyday living (Vila et al., 2004) and is closely related to health status. Along with asthma symptoms and other clinical indicators, QOL measurements are important when assessing asthmatic children and their caregivers holistically (Juniper, Guyatt, Feeny, Ferrie, & Townsend, 1996). This descriptive, crosssectional study examines the effect of asthma severity on caregivers' QOL using the Paediatric Asthma Caregiver's Quality of Life Questionnaire (PACQLQ) of Juniper et al. (1996), which considers activity limitation and emotional function. The PACQLQ also examines the relationship between caregivers' QOL and caregiver sociodemographic characteristics.
Asthma is one of the most common chronic diseases in the United States, affecting about 22.2 million people, 6.5 million of which were children, in 2005 (National Center for Health Statistics [NCHS], 2007). School-age children with asthma are affected by the frequency and severity of episodes, hospital admissions, side effects of medications, morbidity and mortality, and costs of hospitalizations (Vila et al., 2004). Asthma also affects other aspects of life, such as school attendance, physical activity, family dynamic, coping style, psychological functioning, and sleep (Marsac, Funk, & Nelson, 2006; Moonie, Sterling, Figgs, & Castro, 2006). Parents as caregivers are responsible for many aspects of their children's care, including symptom observation, medication administration, and transportation to health care services (Halterman et al., 2004). Because asthma is a chronic condition, parents can experience long-term stressors that impact work productivity, medical decisionmaking, and overall care and discipline issues (Halterman et al., 2004; Laforest et al., 2004). In addition, other sociodemographic factors such as marital status, smoking status, educational level and income, presence of family and support systems, presence of other children in the household, and the parents being diagnosed with asthma themselves can contribute to changes in parental
⁎ Corresponding author. Tel.: +1 702 895 3810; fax: +1 702 895 4807. E-mail addresses: [email protected] (N.S. Cerdan), [email protected] (P.T. Alpert), [email protected] (S. Moonie), [email protected] (D. Cyrkiel), [email protected] (S. Rue). 0897-1897/$ – see front matter. Published by Elsevier Inc. doi:10.1016/j.apnr.2011.01.002
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QOL. Many studies show that childhood morbidity and mortality related to asthma are associated with being lowincome families, being a minority, and living in the inner city (NCHS, 2007). To date, research results relating asthma characteristics including clinical measures and or symptoms and PACQLQmeasured QOL are inconsistent. Developed in Canada by Juniper et al. (1996), the PACQLQ showed acceptable levels of correlation between asthma status and parental QOL. Results showed that the PACQLQ was able to detect QOL changes over time (p b .001) and detect stability in those who did not change (p b .0001). Following school-age children through the school year in the United States., Halterman et al. (2004) showed that baseline asthma severity measured by asthma severity symptoms (i.e., daytime and nighttime symptoms, the need for rescue inhaler use, and the number of symptom-free days) significantly correlated with the PACQLQ score (range r = .23–.51, all p b .1). The highest correlation was between symptom-free days and parental QOL (r = .51, p b .001). At the end of the school year, significant correlations were found with all measures of asthma severity, except for rescue inhaler use. An increase in symptom-free days over time correlated with an improvement in PACQLQ scores (r = .30, p b .001). Conversely, an increase in daytime (r = −.27, p = b.001) and nighttime (r = −.22, p = .005) symptoms correlated with lower PACQLQ scores. Over a 3-month period, Osman, Baxter-Jones, and Helms (2001) showed a significant correlation between a change in children's asthma symptoms and PACQLQ scores (r = .54–.57, p b .001) even if the PACQLQ scores were not clinically significant. This suggests that other social and or psychological factors, in addition to asthma severity, may influence PACQLQ scores (Vila et al., 2004). Many studies relate children's asthma prevalence to sociodemographic characteristics such as minority families living in low-income urban neighborhoods (Akinbami & Schoendorf, 2002). One study suggests that the prevalence and severity of asthma are associated with being African American or Hispanic and to poverty-related factors such as young maternal age, secondhand exposure to cigarette smoke, low birth weight, and living in crowded inner cities (Williams, Sternthal, & Wright, 2009). Erickson et al. (2002) showed that household income and lower perceived asthma severity were statistically significant predictors of QOL as measured by the PACQLQ. Longer length of time diagnosed with asthma, longer length of time enrolled in a specialty clinic, fewer siblings living in the household, and greater convenience of seeing the physician were all related to higher QOL. Using Carstair's deprivation scores to describe the sociodemographics of the families in their study, Osman et al. (2001) found that younger mothers, those who come from less affluent families, and those with greater social deprivation had lower PACQLQ scores. Parental work absenteeism related to the child's illness can have economical
implications for parents (Dean, Calimlim, Kindermann, Khandker, Tinkelman, 2009; Laforest et al., 2004). This study is different from other studies that utilized the PACQLQ because this study used the current National Asthma Education and Prevention Program (NAEPP) guidelines in diagnosing asthma severity in children. The guidelines categorize patients based on worsening physical symptoms such as increased nighttime awakenings, increased use of rescue medication for symptom control, interference with normal activity, and decreased lung function. Very few studies have documented asthma severity using NAEPP guidelines, and for those that did, they have had inadequate sample sizes. In addition, this study uses several measurement tools and clinical indices such as pulmonary function tests (PFTs), whereas other studies depended solely on self-reported asthma severity or administrative records, which can underestimate asthma prevalence. Lastly, the current QOL literature for asthma is conflicted and not highly abundant, so this study lends greater insight to the current research literature. This study is important to nursing because it offers a more holistic focus when addressing asthmatic children and their parents in the clinical setting. Operationalizing parental QOL measures as functional limitations and emotional dimensions allows nurse researchers to quantify the degree of burden that parents experience so that more effective asthma programs can be developed (Halterman et al., 2004). In addition, being familiar with the NAEPP (2007) guidelines in daily practice, nurses can better identify at-risk parents of asthmatic children to more quickly implement appropriate care. QOL has been shown to be an important outcome measure, and being aware of its effect on the individual is important for adherence to medical treatment (Marsac et al., 2006). The objective of this study was to examine the effect of children's asthma severity and sociodemographic factors on parental QOL measured through the PACQLQ.
3. Research design and methodology This correlational study utilized a convenience sample of parents of children and adolescents, aged 7 to 17 years, with medical diagnoses of mild intermittent to severe persistent asthma. This study was reviewed and approved by the institutional review board at the University of Nevada, Las Vegas. From August 2008 to February 2009, participants were chosen from a pediatric pulmonology outpatient clinic located in Las Vegas, Nevada. Parents of children aged from 7 to 17 years were targeted because parents with children in this age range were used to validate the PACQLQ (Juniper et al., 1996). Parents surveyed were legal guardians of the asthmatic children. The clinic was chosen by the investigators because the clinic had patients with a greater variety of asthma severity (i.e., mild, moderate, or severe) and sociodemographic factors (i.e., health insurance coverage, parental age and ethnicity, and other variables). Children
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with a diagnosis of other chronic conditions such as depression, cerebral palsy, diabetes, hypothyroidism, and cancer were excluded from the study. Because most children with asthma also have atopic conditions such as eczema, allergy, and rhinoconjunctivitis, patients with atopy were not excluded from this study (Reichenberg & Broberg, 2001). One of the researchers reviewed the charts of all scheduled patients to verify asthma diagnosis and age. Those deemed to be eligible to participate were approached in the waiting room by the researcher as patients and parents came in for their scheduled appointments. All potential participants were told that the researcher was not an employee of the clinic. They were also told that their participation was voluntary and declining participation would not jeopardize their relationship with their doctor or office staff. Those who agreed to participate completed the informed consent and their children offered assent. Participants were asked to confirm the age of their children and their children's asthma diagnosis. They were also asked their relationship to the children and were excluded if they were not the biological parents, adoptive parents, stepparents, legal guardians, or foster parents. Only one set of questionnaires were completed for each family. Prior to completing the three questionnaires, the researcher gave parents explicit instructions on how to answer the items for each questionnaire, including the option not to answer questions that made them feel uncomfortable. If participants had questions after they started completing the questionnaires, they were told to choose the answer that they most strongly agreed with. To maintain participant confidentiality, participant questionnaires were assigned numbers, and participant names or any other identifying information such as address, telephone number, or birth date were not recorded. The parents returned the questionnaires to the researcher in an unmarked manila envelope to further ensure confidentiality. The three questionnaires utilized were as follows: (1) the PACQLQ (Juniper et al., 1996), (2) the asthma severity questionnaire, and (3) the sociodemographic factors questionnaire. The PACQLQ, a 13-item questionnaire, measures activity limitation and emotional function. This tool is frequently utilized to measure the burden that parents experience in caring for their asthmatic children (aged 7 to 17 years). Specifically, this tool measures how a child's asthma interferes with the parent's daily activities (activity limitation) and the emotions generated (emotional function). The questionnaire contains four items addressing activity limitations and nine items addressing emotional function, with all questions being weighed equally. Parents respond to this questionnaire using a 7-point Likert-type scale, where 1 represents severe impairment and 7 represents no impairment. Examples of questions include the following: “How often did your child's asthma interfere with your job or work around the house?” and “How often were you bothered because your child's asthma interfered with family relationships?” The PACQLQ score produced a mean
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activity limitation score, a mean emotional function score, and a total mean score (Juniper et al., 1996). The questionnaire has been studied to be reliable and valid in certain populations. The PACQLQ has good reliability, with an intraclass correlation coefficient for overall QOL = .85, emotional function = .80, and activity limitation = .84 (Juniper et al., 1996). The Asthma Severity Questionnaire was developed by the researchers for use in this study and includes 18 questions to categorize the child's asthma severity, which mirrors the 2007 NAEPP asthma classification guidelines. The NAEPP asthma classifications include intermittent asthma, mild persistent asthma, moderate persistent asthma, and severe persistent asthma. The NAEPP guidelines to classify asthma severity were turned into questions. Examples of questions included the following: “In the past 30 days, how often has your child had asthma symptoms such as wheezing, coughing, and shortness of breath during the day? and “In the past 30 days, how often did your child wake up during the night due to asthma symptoms such as wheezing, coughing, and shortness of breath?” Participants were also asked about medication use within the past week to verify appropriate classification severity-specific treatment based on NAEPP guidelines. Other questions (not specific to the NAEPP guidelines), such as the number of days of school the child has missed, the number of days spent in the emergency room (ER) or hospital, and parental perception of asthma severity and control, were included based on findings of a literature review. The questionnaire was reviewed by two content experts but was not piloted prior to use in this study. In addition, spirometry readings, including forced expiratory volume in one second (FEV1) and Forced expiratory volume in one second/forced vital capacity ration (FEV1/ FVC) ratios, were obtained from the children's medical records with the permission of the pediatric pulmonologist and informed consent from the parents to further categorize the children's asthma severity based on the NAEPP guidelines. The Sociodemographic Factor Questionnaire, developed by this study's investigators, was based on literature identification of the demographic variables associated with asthma morbidity and mortality. This questionnaire asked 18 questions on age, ethnicity, income, education level, place of residence, employment, health insurance coverage, social support, and other variables. 3.1. Data analysis Data entry and analyses were performed utilizing the Statistical Package for the Social Sciences Version 17.0. To assess the relationship between asthma severity and parental QOL, Spearman's correlation (ρ), analysis of variance (ANOVA), and linear and multivariate regressions were performed. To determine the relationship between sociodemographic factors and parental QOL, Spearman's correlation (ρ), chi-square, and independent t tests were performed.
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4. Results
Table 2 Demographic characteristics by percentages (n = 101)
A total of 112 parents who met the study criteria were invited to participate in the study. Ten parents were not interested in participating in the study and one parent did not return the survey to the researcher. Of the original 114 parents invited, 101 (88.59%) participated in the study. Tables 1 and 2 show the demographic characteristics of the participants. The Cronbach alpha coefficient for the PACQLQ was .89 of the total score, which suggests good internal consistency. Before correlation analyses on the data were performed, scatterplots were generated and checked for violation of assumptions of normality, linearity, and homoscedasticity. Using Spearman's correlation (ρ), significant negative correlations were found between overall asthma severity and mean activity limitation scores (ρ = −.400, p b .001), mean emotional function scores (ρ = −.258, p b .001), and mean total PACQLQ scores (ρ = −.342, p b .001). Significant moderate, negative correlations were found between PACQLQ scores and asthma day symptoms, asthma night symptoms, and asthma exercise symptoms. As asthma severity and other asthma factors increased, PACQLQ scores decreased, indicating poorer QOL. No significant relationships were found between PFT scores and PACQLQ scores. In addition, significant positive correlations were found between employment income and mean activity limitation scores (moderate correlation, ρ = .363, p b .001), mean emotional function scores (small correlation, ρ = .291, p b .05), and mean total PACQLQ scores (moderate correlation, ρ = .346, p b .001). This indicates that parents with higher incomes experience increased QOL. Table 3 provides the details of these analyses. ANOVA was used to compare mean PACQLQ scores for each asthma severity group. Participants were divided based on asthma severity rating prescribed according to NAEPP guidelines. The assumption of homogeneity of variance was not violated. The overall PACQLQ scores were statistically significant for the four asthma severity groups, F(2, 101) = 4.942, p = .003. The effect size, calculated using eta squared, was .132. Post hoc comparisons using Tukey's honestly
Caregiver or child characteristics
Table 1 Demographic characteristics by means (n = 101) Caregiver or child characteristics Child Age (years) Length of diagnosis (years) ER visits in the past year Hospitalizations in the past year School days missed in the past year Caregiver Age (years) Workdays missed in the past year Number of people living in home Number of children living in home
M
SD
10.26 6.49 1.01 0.25 5.85
2.78 3.90 1.98 0.79 9.24
39.34 4.46 3.67 2.63
7.71 7.43 1.78 1.21
Child Male Female Caregiver Male Female Age ≤30 years N30 years Martial status Single Married Separated/Divorced Living with significant other Ethnicity White/Caucasian Hispanic Black/African Other Caregiver type Mother Father Other Parent perception of control Owning a vehicle Language English Spanish English and Spanish Parent with medically diagnosed asthma Family history of asthma Smokers Employed Work hours per weeka b40 ≥40 Education High school College Graduate school Annual incomea Less than $30,000 $30,000 to $45,000 $45,000 to $60,000 $60,000 to $75,000 Greater than $75,000 Insurance No insurance Medicaid Private insurance Ability to pay for health expenses Residence type Own Rent Family or friend support a
% 55.4 44.6 20.8 79.2 11.9 87.1 12.9 64.4 18.8 4.0 58.4 20.8 15.8 5.0 75.2 18.8 6.0 74.3 95 89.1 4.0 5.9 38.6 73.3 9.9 69.3 24.5 42.1 32.7 58.4 8.9 15.8 18.8 10.9 9.9 12.0 5.0 16.8 78.2 86.1 68.3 29.7 88.1
n = 72.
significant different (HSD) test indicated that the mean score for the mild intermittent group (M = 5.25, SD = 1.18) was significantly different from that of the moderate persistent group (M = 4.31, SD = 1.21) and that of the severe persistent
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137 Table 3 Correlation between asthma severity rating and PACQLQ scores
Table 5 Univariate regression model predicting QOL
Asthma severity measure
Activity limitation subscale (ρ)
Emotional function subscale (ρ)
PACQLQ summary scores (ρ)
Asthma severity Day symptoms Exercise symptoms Night symptoms Rescue inhaler use ER visits Hospitalization days Parental perception of asthma severity Parental perception of control School days missed Workdays missed Annual income
−.40⁎⁎ −.43⁎⁎ −.44⁎⁎ −.48⁎⁎ −.31⁎⁎ −.45⁎⁎ −.22⁎ −.58⁎⁎
−.26⁎⁎ −.29⁎⁎ −.30⁎⁎ −.33⁎⁎ ns −.41⁎⁎ −.20⁎ −.49⁎⁎
−.34⁎⁎ −.37⁎⁎ −.39⁎⁎ −.43⁎⁎ ns −.46⁎⁎ −.24⁎ −.58⁎⁎
−.37⁎⁎ −.36⁎⁎ −.49⁎⁎ .36⁎⁎
−.28⁎⁎ −.24⁎⁎ −.24⁎ .29⁎
−.34⁎⁎ −.31⁎⁎ −.37⁎⁎ .35⁎⁎
Note. ρ = Spearman ρ; ns = not significant. ⁎ p b 0.05. ⁎⁎ p b 0.001.
group (M = 4.11, SD = 1.49). Table 4 provides the details of these analyses. ANOVAs to compare activity limitation scores showed statistical significance in overall PACQLQ scores for the four asthma severity groups, F(3, 101) = 7.56, p = .0005. The effect size, calculated using eta squared, was .189. Post hoc comparisons using Tukey's HSD test indicated that the mean score for the mild intermittent group (M = 5.37, SD = 1.31) was significantly different from that of the moderate persistent group (M = 4.02, SD = 1.75) and that of the severe persistent group (M = 3.55, SD = 1.91). The mild persistent group (M = 5.13, SD = 1.25) was significantly different from the severe persistent group (M = 3.55, SD = 1.91). ANOVA comparisons of emotional function scores showed statistical significance in PACQLQ scores for the four asthma severity groups, F(3, 101) = 2.855, p = .041. The effect size, calculated using eta squared, was .08. Post hoc comparisons using Tukey's HSD test showed no significant differences among the four groups of asthma severity. Univariate linear regression was used to determine which asthma severity and sociodemographic factors predicted
Table 4 PACQLQ scores and researcher rating of asthma severity Asthma severity rating by caregiver
Activity limitation subscale, M (SD)a
Emotional function subscale, M (SD)b
PACQLQ summary scores, M (SD)c
Mild intermittent Mild persistent Moderate persistent Severe persistent
5.37 (1.31) 5.13 (1.25) 4.02 (1.75) 3.55 (1.91)
5.20 (1.22) 4.68 (1.14) 4.43 (1.14) 4.36 (1.51)
5.25 (1.18) 4.82 (0.95) 4.31 (1.21) 4.11 (1.49)
a b c
df = 3, F = 7.56, p = .0005, η2 = .189. df = 3, F = 2.855, p = .041, η2 = .08. df = 2, F = 4.942, p = .003, η2 = .132.
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Predictor
Annual income Hospitalization days ER visits School days missed Workdays missed
Activity limitation subscale
Emotional function subscale
PACQLQ summary scores
B
R2
B
R2
B
R2
.23 −.57 −.33 −.08 −.11
.08⁎⁎⁎ .06⁎ .15⁎⁎ .18⁎⁎ .21⁎⁎
ns ns −.20 −.03 −.04
ns ns .09⁎⁎ .04⁎ .05⁎
.14 −.30 −.24 −.05 −.06
.05⁎ .03⁎⁎ .13⁎⁎ .10⁎⁎⁎ .12⁎
Note. B = unstandardized beta coefficient; R2 = adjusted r2; ns = not significant. ⁎ p b 0.05. ⁎⁎ p b 0.005. ⁎⁎⁎ p b 0.001.
parental QOL scores. Prior to performing linear regression, the data set was assessed for multicollinearity, singularity, outliers, normality, linearity, homoscedasticity, and independence of residuals. Predictor of better QOL included increased income. Factors predicting poor QOL included increased hospitalization days, increased ER visits, and increased school days and workdays missed (Table 5). The significant variables (i.e., income, ER visits, hospitalization days, school days missed, and workdays missed) were further tested using multiple linear regression. Relationships between ER visits and mean total PACQLQ scores, mean activity limitation scores, and mean emotional function scores were significant. The correlation between the mean activity limitation score and workdays missed (β = −.069, p b .043, r2 = .317) was also significant (Table 6). Independent t tests were performed to compare the mean PACQLQ scores between different paired groups of sociodemographic factors (i.e., male vs female, owning a home vs renting, and other groups). Prior to performing the data analyses, the samples were checked for normal distribution, homogeneity of variance, independence of observations, and level of measurement. Parents who were not Black or African, owned a car, were able to pay health costs, owned a home, and perceived their children's asthma as under control had higher mean total, mean activity limitation, and mean emotional function PACQLQ scores.
Table 6 Multiple regression models predicting QOL Predictor
ER visits Workdays missed
Activity limitation subscale
Emotional function subscale
PACQLQ summary scores
B
R2
B
R2
B
R2
−.25 −.07
.32⁎ .32⁎
−.18 ns
.08⁎ ns
−.20 ns
.19⁎ ns
Note. B = unstandardized beta coefficient; R2 = adjusted r2; ns = not significant. ⁎ p b 0.05.
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5. Discussion The main finding in this study is that higher levels of asthma severity reflected decreased PACQLQ scores, or decreased parental QOL. This current study affirms findings by Williams et al. (2000), who also found a negative correlation between PACQLQ scores for parents and their children's asthma severity scores over a period of 4 months (r = −.39, p b .001). They also found that PACQLQ scores were correlated negatively with the number of days missed from school (r = −.24, p b .001), which this study supports. One explanation may be that parental QOL is affected by concerns of rising medical expenses with increasing asthma severity, stress related to the disease process, availability of social support, access to medical care and appropriate medication, and the impact of asthma on daily activities in the home (Annett, Bender, DuHamel, & Lapidus, 2003; Erickson et al., 2002). Participants grouped by asthma severity according to NAEPP guidelines showed significant differences in PACQLQ scores. As asthma severity increased, mean parental PACQLQ scores decreased, indicating decreased QOL (df = 3, F = 7.56, p = .0005, η2 = .189). This finding indicates that parents of children with mild asthma claimed better QOL. This suggests that children with higher asthma severity require levels of care that place greater activity restriction and emotional responsibility on parents. In this current study, several sociodemographic factors were shown to influence parental QOL, some of which do not support current findings in the literature. For example, increased ER visits were significantly related to decreased overall QOL in this study. This is contrary to findings by Halterman et al. (2004), who identified increased symptomfree days and the parental perceptions of asthma control. They did not find ER visits to be a significant factor associated with parental QOL. Instead, their predictive factors of worse QOL included Hispanic ethnicity, use of daily maintenance medication, and secondhand smoke exposure in the home. Research by Erickson et al. (2002) and Annett et al. (2003) were more closely aligned with findings from this study. Several studies suggested that the prevalence and severity of asthma are associated with ethnicity and poverty-related factors such as young maternal age, maternal cigarette smoking, low birth weight, and living in crowded conditions in the inner city (Williams et al., 2009). This study supported the idea that sociodemographic factors also influence parental perception of QOL. A family history of asthma; being single, divorced, or widowed; and perceived poor asthma control yielded significantly lower PACQLQ scores. Correlational analyses of mean PACQLQ scores and sociodemographic factors revealed different findings from other studies. For example, Osman et al. (2001) found sociodemographic factors such as being a young mother, being from less affluent families, and having increased socioeconomic deprivation scores also scored lower on the
PACQLQ. Dalheim-Englund, Rydstrom, Rasmussen, Moller, and Sandman (2004) found another set of sociodemographic factors; place of residence, age of the child, and severity of the child's asthma impacted PACQLQ scores. These findings suggest that many factors in addition to asthma severity can influence parental QOL, which is similar to this study's findings. The strengths of this study included the close timing of actual events and responses to the questionnaires. The PACQLQ and asthma severity questionnaires ask questions within the past week and past month, respectively. Because parents would better remember important events related to their children's asthma within these time frames, this reduced the risk of recall error and improved accuracy of reporting the data (Reichenberg & Broberg, 2001). The PACQLQ was studied to be both reliable and responsive with moderate validity (Juniper et al., 1996), which strengthened the results obtained. Many studies used the PACQLQ showing reliability and validity (Dalheim-Englund et al., 2004; Laforest et al., 2004; Osman et al., 2001; Reichenberg et al., 2001). This study had several limitations. First, utilizing a crosssectional study design provides a snapshot of the lives of children with asthma and their parents at a specific point in time, and answers to the questionnaires could have been different if a longer period or a different period (seasonal influence of certain types of asthma) was used (DalheimEnglund et al., 2004; Reichenberg et al., 2001). Ideally, a longitudinal research study would provide ongoing changes in QOL as related to changes in life events related to asthma. Another limitation is selection bias because some parents were more willing to participate in the study due to the manifestation of their children's asthma severity.
6. Conclusion and recommendations The evidence presented in this study supports the idea that numerous factors such as asthma severity and sociodemographic factors are capable of influencing QOL. Measuring parental QOL can help to develop more effective asthma programs that take the experiences of parents into consideration (Halterman et al., 2004), an important component for successful medical and nursing care. One area for future research is to test a larger number of participants over a longer period in multiple settings. Examining a larger number of participants in different settings allows assessment for study consistency, and the longitudinal design may account for changing sociodemographic and asthma severity on QOL. Several other measures such as parents' own physical disabilities, coping abilities, psychological health, family context, and other unknown factors may be revealed in a longitudinal study design. Recent studies suggest that psychological factors and parents' mental health influence PACQLQ scores and health care utilization for their asthmatic children (Dalheirm-Englund et al., 2004;
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Vila et al., 2004). Thus, another area for future research should be to examine other factors besides asthma severity and sociodemographic factors that may influence QOL. To determine if other factors influence QOL, instrumentation research to develop other measurement tools aside from the PACQLQ needs to occur. Supporting previous research findings, this current study helped affirm the idea that nurses working with families of asthmatic children need to aggressively provide care through patient education and vigilant monitoring. This study showed that asthma severity is closely aligned with parental QOL. Understanding this relationship, nurses can positively influence care by assuring tight control of asthma severity, and even reversing the asthma severity category of patients has the potential to elevate QOL for both parents and asthmatic children especially in families that are the most vulnerable. References Akinbami, L. J., & Schoendorf, K. C. (2002). Trends in childhood asthma: Prevalence, health care utilization, and mortality. Pediatrics 110, 315–322. Annett, R. D., Bender, B. G., DuHamel, T. R., & Lapidus, J. (2003). Factors influencing parent reports on quality of life for children with asthma. Journal of Asthma 40, 577–587. Dalheim-Englund, A., Rydstrom, I., Rasmussen, B. H., Moller, C., & Sandman, P. (2004). Having a child with asthma—Quality of life for Swedish parents. Journal of Clinical Nursing 13, 386–395. Dean, B. B., Calimlim, B. M., Kindermann, S. L., Khandker, R. K., & Tinkelman, D. (2009). The impact of uncontrolled asthma on absenteeism and health-related quality of life. Journal of Asthma 46, 861–866. Erickson, S. R., Munzenberger, P. J., Plante, M. J., Kirking, D. M., Hurwitz, M., & Vanuya, R. Z. (2002). Influence of sociodemographic factors on the health-related quality of life of pediatric patients with asthma and their caregivers. Journal of Asthma 39, 107–117.
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Halterman, J. S., Yoos, H. L., Conn, K. M., Callahan, P. M., Montes, G., & Neely, T. L., et al. (2004). The impact of childhood asthma on parental quality of life. Journal of Asthma 41, 645–653. Juniper, E. F., Guyatt, G. H., Feeny, P. J., Ferrie, L. E., & Townsend, M. (1996). Measuring quality of life in the parents of children with asthma. Quality of Life Research 5, 27–34. Laforest, L., Yin, D., Kocevar, V. S., Pacheco, Y., Dickson, N., & Gormand, F, et al. (2004). Association between asthma control in children and loss of workdays by caregivers. Annals of Allergy, Asthma, and Immunology 93, 265–271. Marsac, M. L., Funk, J. B., & Nelson, L. (2006). Coping styles, psychological functioning and quality of life in children with asthma. Child: Care, Health and Development 33, 360–367. Moonie, S., Sterling, D. A., Figgs, L. W., & Castro, M. (2006). Asthma status and severity affects missed school days. Journal of School Health 76, 18–24. National Asthma Education and Prevention Program (NAEPP). (2007). Guidelines for the diagnosis and management of asthma (EPR-3). Retrieved June 11, 2008, from http://www.nhlbi.nih.gov/guidelines/ asthma/index.htm. National Center for Health Statistics (NCHS). (2007). Asthma prevalence, health care use and mortality: United States, 2003–2005. Retrieved May 18, 2008, from http://www.cdc.gov/nchs/products/pubs/pubd/hestats/ ashtma03-05/asthma03-05.htm. Osman, L. M., Baxter-Jones, A. D. G., & Helms, P. J. (2001). Parents' quality of life and respiratory symptoms in young children with mild wheeze. European Respiratory Journal 17, 254–258. Reichenberg, K., & Broberg, A. G. (2001). The Paediatric Asthma Caregiver's Quality of Life Questionnaire in Swedish parents. Acta Paediatrica, International Journal of Paediatrics 90, 45–50. Vila, G., Hayder, R., Bertrand, C., Falissard, B., De Blic, J., & MourenSimeoni, M., et al. (2004). Psychopathology and quality of life for adolescents with asthma and their parents. Psychosomatics 44, 319–328. Williams, D. R., Sternthal, M., & Wright, R. J. (2009). Social determinants: Taking the social context of asthma seriously. Pediatrics 123, S174–S184. Williams, S., et al. (2000). Effect of asthma on the quality of life among children and their caregivers in the Atlanta Empowerment Zone. Journal of Urban Health: Bulletin of the New York Academy of Medicine 77, 268–279.
Applied Nursing Research 25 (2012) 131 – 137 www.elsevier.com/locate/apnr
Original Articles
Asthma severity in children and the quality of life of their parents Noelle S. Cerdan, RN, CPNPa , Patricia T. Alpert, DrPH, APNb,⁎, Sheniz Moonie, PhDc , Dianne Cyrkiel, MSN, APNd , Shona Rue, MSN, CPNPd a Oshiro Pediatrics, Las Vegas, NV 89119-6183, USA School of Nursing, University of Nevada, Box 453018, Las Vegas, NV 8154-3018, USA c School of Community Health Sciences, University of Nevada, Box 453063 Las Vegas, NV 89154-3063, USA d School of Nursing, University of Nevada, Box 453018, Las Vegas, NV 8154-3018, USA Received 31 March 2010; revised 3 January 2011; accepted 17 January 2011 b
Abstract
This study examines the effect of asthma severity of children aged 7–17 years and sociodemographic characteristics on the caregiver's quality of life. For parents of asthmatic children, there was a negative correlation between overall asthma severity and quality-of-life score. Measuring parental quality of life enables the development of effective asthma programs. Published by Elsevier Inc.
1. Introduction
2. Background
Quality of life (QOL) can be described as general satisfaction with everyday living (Vila et al., 2004) and is closely related to health status. Along with asthma symptoms and other clinical indicators, QOL measurements are important when assessing asthmatic children and their caregivers holistically (Juniper, Guyatt, Feeny, Ferrie, & Townsend, 1996). This descriptive, crosssectional study examines the effect of asthma severity on caregivers' QOL using the Paediatric Asthma Caregiver's Quality of Life Questionnaire (PACQLQ) of Juniper et al. (1996), which considers activity limitation and emotional function. The PACQLQ also examines the relationship between caregivers' QOL and caregiver sociodemographic characteristics.
Asthma is one of the most common chronic diseases in the United States, affecting about 22.2 million people, 6.5 million of which were children, in 2005 (National Center for Health Statistics [NCHS], 2007). School-age children with asthma are affected by the frequency and severity of episodes, hospital admissions, side effects of medications, morbidity and mortality, and costs of hospitalizations (Vila et al., 2004). Asthma also affects other aspects of life, such as school attendance, physical activity, family dynamic, coping style, psychological functioning, and sleep (Marsac, Funk, & Nelson, 2006; Moonie, Sterling, Figgs, & Castro, 2006). Parents as caregivers are responsible for many aspects of their children's care, including symptom observation, medication administration, and transportation to health care services (Halterman et al., 2004). Because asthma is a chronic condition, parents can experience long-term stressors that impact work productivity, medical decisionmaking, and overall care and discipline issues (Halterman et al., 2004; Laforest et al., 2004). In addition, other sociodemographic factors such as marital status, smoking status, educational level and income, presence of family and support systems, presence of other children in the household, and the parents being diagnosed with asthma themselves can contribute to changes in parental
⁎ Corresponding author. Tel.: +1 702 895 3810; fax: +1 702 895 4807. E-mail addresses: [email protected] (N.S. Cerdan), [email protected] (P.T. Alpert), [email protected] (S. Moonie), [email protected] (D. Cyrkiel), [email protected] (S. Rue). 0897-1897/$ – see front matter. Published by Elsevier Inc. doi:10.1016/j.apnr.2011.01.002
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QOL. Many studies show that childhood morbidity and mortality related to asthma are associated with being lowincome families, being a minority, and living in the inner city (NCHS, 2007). To date, research results relating asthma characteristics including clinical measures and or symptoms and PACQLQmeasured QOL are inconsistent. Developed in Canada by Juniper et al. (1996), the PACQLQ showed acceptable levels of correlation between asthma status and parental QOL. Results showed that the PACQLQ was able to detect QOL changes over time (p b .001) and detect stability in those who did not change (p b .0001). Following school-age children through the school year in the United States., Halterman et al. (2004) showed that baseline asthma severity measured by asthma severity symptoms (i.e., daytime and nighttime symptoms, the need for rescue inhaler use, and the number of symptom-free days) significantly correlated with the PACQLQ score (range r = .23–.51, all p b .1). The highest correlation was between symptom-free days and parental QOL (r = .51, p b .001). At the end of the school year, significant correlations were found with all measures of asthma severity, except for rescue inhaler use. An increase in symptom-free days over time correlated with an improvement in PACQLQ scores (r = .30, p b .001). Conversely, an increase in daytime (r = −.27, p = b.001) and nighttime (r = −.22, p = .005) symptoms correlated with lower PACQLQ scores. Over a 3-month period, Osman, Baxter-Jones, and Helms (2001) showed a significant correlation between a change in children's asthma symptoms and PACQLQ scores (r = .54–.57, p b .001) even if the PACQLQ scores were not clinically significant. This suggests that other social and or psychological factors, in addition to asthma severity, may influence PACQLQ scores (Vila et al., 2004). Many studies relate children's asthma prevalence to sociodemographic characteristics such as minority families living in low-income urban neighborhoods (Akinbami & Schoendorf, 2002). One study suggests that the prevalence and severity of asthma are associated with being African American or Hispanic and to poverty-related factors such as young maternal age, secondhand exposure to cigarette smoke, low birth weight, and living in crowded inner cities (Williams, Sternthal, & Wright, 2009). Erickson et al. (2002) showed that household income and lower perceived asthma severity were statistically significant predictors of QOL as measured by the PACQLQ. Longer length of time diagnosed with asthma, longer length of time enrolled in a specialty clinic, fewer siblings living in the household, and greater convenience of seeing the physician were all related to higher QOL. Using Carstair's deprivation scores to describe the sociodemographics of the families in their study, Osman et al. (2001) found that younger mothers, those who come from less affluent families, and those with greater social deprivation had lower PACQLQ scores. Parental work absenteeism related to the child's illness can have economical
implications for parents (Dean, Calimlim, Kindermann, Khandker, Tinkelman, 2009; Laforest et al., 2004). This study is different from other studies that utilized the PACQLQ because this study used the current National Asthma Education and Prevention Program (NAEPP) guidelines in diagnosing asthma severity in children. The guidelines categorize patients based on worsening physical symptoms such as increased nighttime awakenings, increased use of rescue medication for symptom control, interference with normal activity, and decreased lung function. Very few studies have documented asthma severity using NAEPP guidelines, and for those that did, they have had inadequate sample sizes. In addition, this study uses several measurement tools and clinical indices such as pulmonary function tests (PFTs), whereas other studies depended solely on self-reported asthma severity or administrative records, which can underestimate asthma prevalence. Lastly, the current QOL literature for asthma is conflicted and not highly abundant, so this study lends greater insight to the current research literature. This study is important to nursing because it offers a more holistic focus when addressing asthmatic children and their parents in the clinical setting. Operationalizing parental QOL measures as functional limitations and emotional dimensions allows nurse researchers to quantify the degree of burden that parents experience so that more effective asthma programs can be developed (Halterman et al., 2004). In addition, being familiar with the NAEPP (2007) guidelines in daily practice, nurses can better identify at-risk parents of asthmatic children to more quickly implement appropriate care. QOL has been shown to be an important outcome measure, and being aware of its effect on the individual is important for adherence to medical treatment (Marsac et al., 2006). The objective of this study was to examine the effect of children's asthma severity and sociodemographic factors on parental QOL measured through the PACQLQ.
3. Research design and methodology This correlational study utilized a convenience sample of parents of children and adolescents, aged 7 to 17 years, with medical diagnoses of mild intermittent to severe persistent asthma. This study was reviewed and approved by the institutional review board at the University of Nevada, Las Vegas. From August 2008 to February 2009, participants were chosen from a pediatric pulmonology outpatient clinic located in Las Vegas, Nevada. Parents of children aged from 7 to 17 years were targeted because parents with children in this age range were used to validate the PACQLQ (Juniper et al., 1996). Parents surveyed were legal guardians of the asthmatic children. The clinic was chosen by the investigators because the clinic had patients with a greater variety of asthma severity (i.e., mild, moderate, or severe) and sociodemographic factors (i.e., health insurance coverage, parental age and ethnicity, and other variables). Children
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with a diagnosis of other chronic conditions such as depression, cerebral palsy, diabetes, hypothyroidism, and cancer were excluded from the study. Because most children with asthma also have atopic conditions such as eczema, allergy, and rhinoconjunctivitis, patients with atopy were not excluded from this study (Reichenberg & Broberg, 2001). One of the researchers reviewed the charts of all scheduled patients to verify asthma diagnosis and age. Those deemed to be eligible to participate were approached in the waiting room by the researcher as patients and parents came in for their scheduled appointments. All potential participants were told that the researcher was not an employee of the clinic. They were also told that their participation was voluntary and declining participation would not jeopardize their relationship with their doctor or office staff. Those who agreed to participate completed the informed consent and their children offered assent. Participants were asked to confirm the age of their children and their children's asthma diagnosis. They were also asked their relationship to the children and were excluded if they were not the biological parents, adoptive parents, stepparents, legal guardians, or foster parents. Only one set of questionnaires were completed for each family. Prior to completing the three questionnaires, the researcher gave parents explicit instructions on how to answer the items for each questionnaire, including the option not to answer questions that made them feel uncomfortable. If participants had questions after they started completing the questionnaires, they were told to choose the answer that they most strongly agreed with. To maintain participant confidentiality, participant questionnaires were assigned numbers, and participant names or any other identifying information such as address, telephone number, or birth date were not recorded. The parents returned the questionnaires to the researcher in an unmarked manila envelope to further ensure confidentiality. The three questionnaires utilized were as follows: (1) the PACQLQ (Juniper et al., 1996), (2) the asthma severity questionnaire, and (3) the sociodemographic factors questionnaire. The PACQLQ, a 13-item questionnaire, measures activity limitation and emotional function. This tool is frequently utilized to measure the burden that parents experience in caring for their asthmatic children (aged 7 to 17 years). Specifically, this tool measures how a child's asthma interferes with the parent's daily activities (activity limitation) and the emotions generated (emotional function). The questionnaire contains four items addressing activity limitations and nine items addressing emotional function, with all questions being weighed equally. Parents respond to this questionnaire using a 7-point Likert-type scale, where 1 represents severe impairment and 7 represents no impairment. Examples of questions include the following: “How often did your child's asthma interfere with your job or work around the house?” and “How often were you bothered because your child's asthma interfered with family relationships?” The PACQLQ score produced a mean
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activity limitation score, a mean emotional function score, and a total mean score (Juniper et al., 1996). The questionnaire has been studied to be reliable and valid in certain populations. The PACQLQ has good reliability, with an intraclass correlation coefficient for overall QOL = .85, emotional function = .80, and activity limitation = .84 (Juniper et al., 1996). The Asthma Severity Questionnaire was developed by the researchers for use in this study and includes 18 questions to categorize the child's asthma severity, which mirrors the 2007 NAEPP asthma classification guidelines. The NAEPP asthma classifications include intermittent asthma, mild persistent asthma, moderate persistent asthma, and severe persistent asthma. The NAEPP guidelines to classify asthma severity were turned into questions. Examples of questions included the following: “In the past 30 days, how often has your child had asthma symptoms such as wheezing, coughing, and shortness of breath during the day? and “In the past 30 days, how often did your child wake up during the night due to asthma symptoms such as wheezing, coughing, and shortness of breath?” Participants were also asked about medication use within the past week to verify appropriate classification severity-specific treatment based on NAEPP guidelines. Other questions (not specific to the NAEPP guidelines), such as the number of days of school the child has missed, the number of days spent in the emergency room (ER) or hospital, and parental perception of asthma severity and control, were included based on findings of a literature review. The questionnaire was reviewed by two content experts but was not piloted prior to use in this study. In addition, spirometry readings, including forced expiratory volume in one second (FEV1) and Forced expiratory volume in one second/forced vital capacity ration (FEV1/ FVC) ratios, were obtained from the children's medical records with the permission of the pediatric pulmonologist and informed consent from the parents to further categorize the children's asthma severity based on the NAEPP guidelines. The Sociodemographic Factor Questionnaire, developed by this study's investigators, was based on literature identification of the demographic variables associated with asthma morbidity and mortality. This questionnaire asked 18 questions on age, ethnicity, income, education level, place of residence, employment, health insurance coverage, social support, and other variables. 3.1. Data analysis Data entry and analyses were performed utilizing the Statistical Package for the Social Sciences Version 17.0. To assess the relationship between asthma severity and parental QOL, Spearman's correlation (ρ), analysis of variance (ANOVA), and linear and multivariate regressions were performed. To determine the relationship between sociodemographic factors and parental QOL, Spearman's correlation (ρ), chi-square, and independent t tests were performed.
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4. Results
Table 2 Demographic characteristics by percentages (n = 101)
A total of 112 parents who met the study criteria were invited to participate in the study. Ten parents were not interested in participating in the study and one parent did not return the survey to the researcher. Of the original 114 parents invited, 101 (88.59%) participated in the study. Tables 1 and 2 show the demographic characteristics of the participants. The Cronbach alpha coefficient for the PACQLQ was .89 of the total score, which suggests good internal consistency. Before correlation analyses on the data were performed, scatterplots were generated and checked for violation of assumptions of normality, linearity, and homoscedasticity. Using Spearman's correlation (ρ), significant negative correlations were found between overall asthma severity and mean activity limitation scores (ρ = −.400, p b .001), mean emotional function scores (ρ = −.258, p b .001), and mean total PACQLQ scores (ρ = −.342, p b .001). Significant moderate, negative correlations were found between PACQLQ scores and asthma day symptoms, asthma night symptoms, and asthma exercise symptoms. As asthma severity and other asthma factors increased, PACQLQ scores decreased, indicating poorer QOL. No significant relationships were found between PFT scores and PACQLQ scores. In addition, significant positive correlations were found between employment income and mean activity limitation scores (moderate correlation, ρ = .363, p b .001), mean emotional function scores (small correlation, ρ = .291, p b .05), and mean total PACQLQ scores (moderate correlation, ρ = .346, p b .001). This indicates that parents with higher incomes experience increased QOL. Table 3 provides the details of these analyses. ANOVA was used to compare mean PACQLQ scores for each asthma severity group. Participants were divided based on asthma severity rating prescribed according to NAEPP guidelines. The assumption of homogeneity of variance was not violated. The overall PACQLQ scores were statistically significant for the four asthma severity groups, F(2, 101) = 4.942, p = .003. The effect size, calculated using eta squared, was .132. Post hoc comparisons using Tukey's honestly
Caregiver or child characteristics
Table 1 Demographic characteristics by means (n = 101) Caregiver or child characteristics Child Age (years) Length of diagnosis (years) ER visits in the past year Hospitalizations in the past year School days missed in the past year Caregiver Age (years) Workdays missed in the past year Number of people living in home Number of children living in home
M
SD
10.26 6.49 1.01 0.25 5.85
2.78 3.90 1.98 0.79 9.24
39.34 4.46 3.67 2.63
7.71 7.43 1.78 1.21
Child Male Female Caregiver Male Female Age ≤30 years N30 years Martial status Single Married Separated/Divorced Living with significant other Ethnicity White/Caucasian Hispanic Black/African Other Caregiver type Mother Father Other Parent perception of control Owning a vehicle Language English Spanish English and Spanish Parent with medically diagnosed asthma Family history of asthma Smokers Employed Work hours per weeka b40 ≥40 Education High school College Graduate school Annual incomea Less than $30,000 $30,000 to $45,000 $45,000 to $60,000 $60,000 to $75,000 Greater than $75,000 Insurance No insurance Medicaid Private insurance Ability to pay for health expenses Residence type Own Rent Family or friend support a
% 55.4 44.6 20.8 79.2 11.9 87.1 12.9 64.4 18.8 4.0 58.4 20.8 15.8 5.0 75.2 18.8 6.0 74.3 95 89.1 4.0 5.9 38.6 73.3 9.9 69.3 24.5 42.1 32.7 58.4 8.9 15.8 18.8 10.9 9.9 12.0 5.0 16.8 78.2 86.1 68.3 29.7 88.1
n = 72.
significant different (HSD) test indicated that the mean score for the mild intermittent group (M = 5.25, SD = 1.18) was significantly different from that of the moderate persistent group (M = 4.31, SD = 1.21) and that of the severe persistent
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137 Table 3 Correlation between asthma severity rating and PACQLQ scores
Table 5 Univariate regression model predicting QOL
Asthma severity measure
Activity limitation subscale (ρ)
Emotional function subscale (ρ)
PACQLQ summary scores (ρ)
Asthma severity Day symptoms Exercise symptoms Night symptoms Rescue inhaler use ER visits Hospitalization days Parental perception of asthma severity Parental perception of control School days missed Workdays missed Annual income
−.40⁎⁎ −.43⁎⁎ −.44⁎⁎ −.48⁎⁎ −.31⁎⁎ −.45⁎⁎ −.22⁎ −.58⁎⁎
−.26⁎⁎ −.29⁎⁎ −.30⁎⁎ −.33⁎⁎ ns −.41⁎⁎ −.20⁎ −.49⁎⁎
−.34⁎⁎ −.37⁎⁎ −.39⁎⁎ −.43⁎⁎ ns −.46⁎⁎ −.24⁎ −.58⁎⁎
−.37⁎⁎ −.36⁎⁎ −.49⁎⁎ .36⁎⁎
−.28⁎⁎ −.24⁎⁎ −.24⁎ .29⁎
−.34⁎⁎ −.31⁎⁎ −.37⁎⁎ .35⁎⁎
Note. ρ = Spearman ρ; ns = not significant. ⁎ p b 0.05. ⁎⁎ p b 0.001.
group (M = 4.11, SD = 1.49). Table 4 provides the details of these analyses. ANOVAs to compare activity limitation scores showed statistical significance in overall PACQLQ scores for the four asthma severity groups, F(3, 101) = 7.56, p = .0005. The effect size, calculated using eta squared, was .189. Post hoc comparisons using Tukey's HSD test indicated that the mean score for the mild intermittent group (M = 5.37, SD = 1.31) was significantly different from that of the moderate persistent group (M = 4.02, SD = 1.75) and that of the severe persistent group (M = 3.55, SD = 1.91). The mild persistent group (M = 5.13, SD = 1.25) was significantly different from the severe persistent group (M = 3.55, SD = 1.91). ANOVA comparisons of emotional function scores showed statistical significance in PACQLQ scores for the four asthma severity groups, F(3, 101) = 2.855, p = .041. The effect size, calculated using eta squared, was .08. Post hoc comparisons using Tukey's HSD test showed no significant differences among the four groups of asthma severity. Univariate linear regression was used to determine which asthma severity and sociodemographic factors predicted
Table 4 PACQLQ scores and researcher rating of asthma severity Asthma severity rating by caregiver
Activity limitation subscale, M (SD)a
Emotional function subscale, M (SD)b
PACQLQ summary scores, M (SD)c
Mild intermittent Mild persistent Moderate persistent Severe persistent
5.37 (1.31) 5.13 (1.25) 4.02 (1.75) 3.55 (1.91)
5.20 (1.22) 4.68 (1.14) 4.43 (1.14) 4.36 (1.51)
5.25 (1.18) 4.82 (0.95) 4.31 (1.21) 4.11 (1.49)
a b c
df = 3, F = 7.56, p = .0005, η2 = .189. df = 3, F = 2.855, p = .041, η2 = .08. df = 2, F = 4.942, p = .003, η2 = .132.
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Predictor
Annual income Hospitalization days ER visits School days missed Workdays missed
Activity limitation subscale
Emotional function subscale
PACQLQ summary scores
B
R2
B
R2
B
R2
.23 −.57 −.33 −.08 −.11
.08⁎⁎⁎ .06⁎ .15⁎⁎ .18⁎⁎ .21⁎⁎
ns ns −.20 −.03 −.04
ns ns .09⁎⁎ .04⁎ .05⁎
.14 −.30 −.24 −.05 −.06
.05⁎ .03⁎⁎ .13⁎⁎ .10⁎⁎⁎ .12⁎
Note. B = unstandardized beta coefficient; R2 = adjusted r2; ns = not significant. ⁎ p b 0.05. ⁎⁎ p b 0.005. ⁎⁎⁎ p b 0.001.
parental QOL scores. Prior to performing linear regression, the data set was assessed for multicollinearity, singularity, outliers, normality, linearity, homoscedasticity, and independence of residuals. Predictor of better QOL included increased income. Factors predicting poor QOL included increased hospitalization days, increased ER visits, and increased school days and workdays missed (Table 5). The significant variables (i.e., income, ER visits, hospitalization days, school days missed, and workdays missed) were further tested using multiple linear regression. Relationships between ER visits and mean total PACQLQ scores, mean activity limitation scores, and mean emotional function scores were significant. The correlation between the mean activity limitation score and workdays missed (β = −.069, p b .043, r2 = .317) was also significant (Table 6). Independent t tests were performed to compare the mean PACQLQ scores between different paired groups of sociodemographic factors (i.e., male vs female, owning a home vs renting, and other groups). Prior to performing the data analyses, the samples were checked for normal distribution, homogeneity of variance, independence of observations, and level of measurement. Parents who were not Black or African, owned a car, were able to pay health costs, owned a home, and perceived their children's asthma as under control had higher mean total, mean activity limitation, and mean emotional function PACQLQ scores.
Table 6 Multiple regression models predicting QOL Predictor
ER visits Workdays missed
Activity limitation subscale
Emotional function subscale
PACQLQ summary scores
B
R2
B
R2
B
R2
−.25 −.07
.32⁎ .32⁎
−.18 ns
.08⁎ ns
−.20 ns
.19⁎ ns
Note. B = unstandardized beta coefficient; R2 = adjusted r2; ns = not significant. ⁎ p b 0.05.
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5. Discussion The main finding in this study is that higher levels of asthma severity reflected decreased PACQLQ scores, or decreased parental QOL. This current study affirms findings by Williams et al. (2000), who also found a negative correlation between PACQLQ scores for parents and their children's asthma severity scores over a period of 4 months (r = −.39, p b .001). They also found that PACQLQ scores were correlated negatively with the number of days missed from school (r = −.24, p b .001), which this study supports. One explanation may be that parental QOL is affected by concerns of rising medical expenses with increasing asthma severity, stress related to the disease process, availability of social support, access to medical care and appropriate medication, and the impact of asthma on daily activities in the home (Annett, Bender, DuHamel, & Lapidus, 2003; Erickson et al., 2002). Participants grouped by asthma severity according to NAEPP guidelines showed significant differences in PACQLQ scores. As asthma severity increased, mean parental PACQLQ scores decreased, indicating decreased QOL (df = 3, F = 7.56, p = .0005, η2 = .189). This finding indicates that parents of children with mild asthma claimed better QOL. This suggests that children with higher asthma severity require levels of care that place greater activity restriction and emotional responsibility on parents. In this current study, several sociodemographic factors were shown to influence parental QOL, some of which do not support current findings in the literature. For example, increased ER visits were significantly related to decreased overall QOL in this study. This is contrary to findings by Halterman et al. (2004), who identified increased symptomfree days and the parental perceptions of asthma control. They did not find ER visits to be a significant factor associated with parental QOL. Instead, their predictive factors of worse QOL included Hispanic ethnicity, use of daily maintenance medication, and secondhand smoke exposure in the home. Research by Erickson et al. (2002) and Annett et al. (2003) were more closely aligned with findings from this study. Several studies suggested that the prevalence and severity of asthma are associated with ethnicity and poverty-related factors such as young maternal age, maternal cigarette smoking, low birth weight, and living in crowded conditions in the inner city (Williams et al., 2009). This study supported the idea that sociodemographic factors also influence parental perception of QOL. A family history of asthma; being single, divorced, or widowed; and perceived poor asthma control yielded significantly lower PACQLQ scores. Correlational analyses of mean PACQLQ scores and sociodemographic factors revealed different findings from other studies. For example, Osman et al. (2001) found sociodemographic factors such as being a young mother, being from less affluent families, and having increased socioeconomic deprivation scores also scored lower on the
PACQLQ. Dalheim-Englund, Rydstrom, Rasmussen, Moller, and Sandman (2004) found another set of sociodemographic factors; place of residence, age of the child, and severity of the child's asthma impacted PACQLQ scores. These findings suggest that many factors in addition to asthma severity can influence parental QOL, which is similar to this study's findings. The strengths of this study included the close timing of actual events and responses to the questionnaires. The PACQLQ and asthma severity questionnaires ask questions within the past week and past month, respectively. Because parents would better remember important events related to their children's asthma within these time frames, this reduced the risk of recall error and improved accuracy of reporting the data (Reichenberg & Broberg, 2001). The PACQLQ was studied to be both reliable and responsive with moderate validity (Juniper et al., 1996), which strengthened the results obtained. Many studies used the PACQLQ showing reliability and validity (Dalheim-Englund et al., 2004; Laforest et al., 2004; Osman et al., 2001; Reichenberg et al., 2001). This study had several limitations. First, utilizing a crosssectional study design provides a snapshot of the lives of children with asthma and their parents at a specific point in time, and answers to the questionnaires could have been different if a longer period or a different period (seasonal influence of certain types of asthma) was used (DalheimEnglund et al., 2004; Reichenberg et al., 2001). Ideally, a longitudinal research study would provide ongoing changes in QOL as related to changes in life events related to asthma. Another limitation is selection bias because some parents were more willing to participate in the study due to the manifestation of their children's asthma severity.
6. Conclusion and recommendations The evidence presented in this study supports the idea that numerous factors such as asthma severity and sociodemographic factors are capable of influencing QOL. Measuring parental QOL can help to develop more effective asthma programs that take the experiences of parents into consideration (Halterman et al., 2004), an important component for successful medical and nursing care. One area for future research is to test a larger number of participants over a longer period in multiple settings. Examining a larger number of participants in different settings allows assessment for study consistency, and the longitudinal design may account for changing sociodemographic and asthma severity on QOL. Several other measures such as parents' own physical disabilities, coping abilities, psychological health, family context, and other unknown factors may be revealed in a longitudinal study design. Recent studies suggest that psychological factors and parents' mental health influence PACQLQ scores and health care utilization for their asthmatic children (Dalheirm-Englund et al., 2004;
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Vila et al., 2004). Thus, another area for future research should be to examine other factors besides asthma severity and sociodemographic factors that may influence QOL. To determine if other factors influence QOL, instrumentation research to develop other measurement tools aside from the PACQLQ needs to occur. Supporting previous research findings, this current study helped affirm the idea that nurses working with families of asthmatic children need to aggressively provide care through patient education and vigilant monitoring. This study showed that asthma severity is closely aligned with parental QOL. Understanding this relationship, nurses can positively influence care by assuring tight control of asthma severity, and even reversing the asthma severity category of patients has the potential to elevate QOL for both parents and asthmatic children especially in families that are the most vulnerable. References Akinbami, L. J., & Schoendorf, K. C. (2002). Trends in childhood asthma: Prevalence, health care utilization, and mortality. Pediatrics 110, 315–322. Annett, R. D., Bender, B. G., DuHamel, T. R., & Lapidus, J. (2003). Factors influencing parent reports on quality of life for children with asthma. Journal of Asthma 40, 577–587. Dalheim-Englund, A., Rydstrom, I., Rasmussen, B. H., Moller, C., & Sandman, P. (2004). Having a child with asthma—Quality of life for Swedish parents. Journal of Clinical Nursing 13, 386–395. Dean, B. B., Calimlim, B. M., Kindermann, S. L., Khandker, R. K., & Tinkelman, D. (2009). The impact of uncontrolled asthma on absenteeism and health-related quality of life. Journal of Asthma 46, 861–866. Erickson, S. R., Munzenberger, P. J., Plante, M. J., Kirking, D. M., Hurwitz, M., & Vanuya, R. Z. (2002). Influence of sociodemographic factors on the health-related quality of life of pediatric patients with asthma and their caregivers. Journal of Asthma 39, 107–117.
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