Description
I need two different versions. each one must be different than the other. The attached files are the instructions and the article you need to finish this assignment.
Unformatted Attachment Preview
NURS 321
Nursing Research & Evidence-Based Practice
Module 2 Individual Case Study Discussion Questions
Chapter 5
Evan and Marlyce have a 4-year-old son (Micah) who has cerebral palsy. Their life is very
challenging because they both have to work and recently lost their home to foreclosure. Micah is
being discharged to home this afternoon, and Marlyce is obviously anxious. Marlyce states, “I
just feel like we are always out of touch when we go home. I have other children to care for, and
we are always on the go.“ This case study is based on a longitudinal qualitative study from
Canada (Woodgae, Edwards, & Ripat, 2012).
1. Propose a qualitative research study purpose that would help the nurse provide better care for
Micah’s family.
2. As the researchers set up a qualitative study for families of patients such as Micah, they used
purposive sampling. What does this mean, including some ideas for inclusion and exclusion
factors?
3. Now that inclusion and exclusion criteria are set for the study, how can the participants be
recruited? How many participants would be necessary?
Chapter 6
Simon is undergoing cardiac catheterization after a heart attack. Throughout his hospital stay,
the case manager asks about resources at home. Much to everyone’s amazement, it is discovered
that Simon is homeless. Simon is supposed to undergo extensive follow-up and cardiac
rehabilitation. Because of the location of this facility, the case manager knows that there are
other situations similar to Simon’s in this community.
1. If the case manager wanted to research Simon’s experience (managing cardiac disease while
being homeless), how might the researcher maintain rigor?
2. Describe a grounded theory study and an ethnographic study structure for Simon’s case.
3. The case manager is using an ethnographic research methodology for patients who are
homeless and have heart disease. Describe the data gathering process.
Chapter 7
Two teenaged girls visit the school nurse and are concerned about acne. Both have tried “things
and food” that their friends told them about, but nothing is working. They are asking for more
information and something that will help with “these totally annoying zits.”
1. Propose using social media to better understand how acne affects teenaged girls.
2. For a researcher collecting data through social media, how might their interaction affect the
results and how could this be avoided?
3. Discuss how the researcher could verify the findings from the qualitative research.
Chapter 8
The nurse recognizes that there has been an increase in the number of urinary tract infections
(UTIs) on one unit of the rehabilitation facility. He heard about a new type of peri-care bath
wipes. The nurse would like to try them as a way of seeing if they help decrease the incidence of
cystitis.
1. What are the independent and dependent variables in this study?
2. List some extraneous variables in this study.
3. How might the nurse ensure randomization of the participants to the experimental or control
groups?
Chapter 9
Mirlande is an 18-year-old woman in the clinic with asthma. She has been in the United States
for 6 months and has gone through three albuterol inhalers and two salmeterol inhalers. The
nurse practitioner is considering treatment strategies for the client.
1. As the nurse practitioner considers research studies about the best treatment option, she is
frustrated that she cannot find purely experimental studies. Is there value in reviewing a
study that used quasi-experimental methodology? Provide rationale for your answer.
2. If the nurse practitioner was unable to find research specifically about the young adult or
older adolescent, what may be an acceptable alternative? Provide rationale for your answer.
3. Propose a study for clients with asthma that would compare using a long-acting inhaler (antiinflammatory) with an oral medication (anti-inflammatory). Describe the methodology if a
Solomon four-group design was used.
Chapter 18
A woman brings in her 8-year-old child, who has a serious history of asthma. The nurse notes
that the mother is tired looking, and the child is very “clingy.” As the nurse asks questions of the
mother, the mother takes a deep breath and looks away. The nurse senses that there is something
concerning the parent. After the nurse says, “You seem pretty tired,” the mother states that she is
worn out from “chasing around all the kids.”
1. On the basis of an appraisal of the article by Cerdan et al (2012), can the nurse assume that
the client’s mother is likely to become divorced? Support your answer.
2. The nurse would like to compare the current research (Cerdan et al, 2012) to a known
evidence-base. What would you recommend?
3. As the nurse reviews the Cerdan et al article, she notes that in previous research, there was no
correlation between the number of emergency department visits and parental quality of life
scores. Conversely, in the Cerdan et al study data, there was a significant correlation. How
should the nurse use this information?
Available online at www.sciencedirect.com
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: cerdann@unlv.nevada.edu (N.S. Cerdan),
patricia.alpert@unlv.edu (P.T. Alpert), sheniz.moonie@unlv.edu
(S. Moonie), dianne.cyrkiel@unlv.edu (D. Cyrkiel), shona.rue@unlv.edu
(S. Rue).
0897-1897/$ – see front matter. Published by Elsevier Inc.
doi:10.1016/j.apnr.2011.01.002
132
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137
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
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137
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
133
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.
134
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137
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)
df = 3, F = 7.56, p = .0005, η2 = .189.
df = 3, F = 2.855, p = .041, η2 = .08.
c
df = 2, F = 4.942, p = .003, η2 = .132.
a
b
135
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.
136
N.S. Cerdan et al. / Applied Nursing Research 25 (2012) 131–137
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
