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THE ASSOCIATION OF PERCIEVED EMOTIONAL
SUPPORT SELF-REGULATION AND ASTHMA HEALTH
RELATED OUTCOMES

presented by

Wanda Gibson-Scipio

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THE ASSOCIATION OF PERCIEVED EMOTIONAL SUPPORT SELF-
REGULATION AND ASTHMA HEALTH RELATED OUTCOMES
By

Wanda Gibson-Scipio

A DISSERTATION
Submitted to
Michigan State University
In partial fulﬁllment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY

College of Nursing

2006

ABSTRACT
THE ASSOCIATION OF PERCIEVED EMOTIONAL SUPPORT SELF-
REGULATION, DISEASE SELF-MANAGMENT AND ASTHMA HEALTH
RELATED OUTCOMES
By

Wanda Gibson-Scipio

The primary purpose of this study was to examine the relationships between
Perceived Emotional Support, Phase of Asthma Self-Regulation Development, and
Disease Self-Management Behavior among urban adolescents with asthma. Additionally
the study sought to determine if Perceived Emotional Support, Phase of Asthma Self-
Regulation Development, and Disease Self-Management were directly or indirectly
associated with health outcomes(emergency department visits, hospitalizations, symptom
days nights awakened and days activity changed due to asthma) and asthma health related
quality of life. The sample consisted of 303 urban adolescents in grades 9-12 from 6 high
schools in Detroit with a diagnosis of asthma and or nationally accepted respiratory
symptom criteria for asthma. Students completed a computerized survey which included
demographic data, and measures of all study variables. Phase of Asthma Self-Regulation
Development was found to be a signiﬁcant predictor of Disease Self-Management and
Asthma Health Related Quality of Life. Phase of Asthma Self-Regulation Development
was also found to moderate the relationship between Perceived Emotional Support and
Disease Self Management. Phase of Asthma Self-Regulation Development was found to
have a negative association with Asthma Health Related Quality of Life. This
relationship was explained by disease severity. PBS was not found to have a signiﬁcant

relationship with Health Outcomes or Asthma Health Related Quality of Life. Results of

this investigation indicate that interventions to promote self-regulation among
adolescents may positively inﬂuence disease self-management behavior and important
quality of life outcomes. Further although a relationship was not found between
Perceived Emotional Support and any of the outcomes of interest, this does not rule out
the potential efﬁcacy for additional investigations to understand the role of disease
speciﬁc emotional support or other social support ﬁmctions in disease self—management

and asthma health related outcomes.

Copyright by
WANDA GIBSON-SCIPIO

2006

ACKNOWLEDGEMENTS

I ﬁrst would like to give honor and thanks to God for giving me the strength and courage
to complete the doctoral program in nursing. I give you the highest praise for watching
over me and my family and for meeting my every need.

Second I thank my family for enduring this process with me. Without your love, support
and sacriﬁces I could not have come to this point in my academic pursuits. You all make
me proud to be a part of your lives each and everyday. There is no greater love and joy
than what we share.
I thank each member of my dissertation committee for your generous support, guidance,
encouragement, mentorship and faith in me and this project. Each of you played a
signiﬁcant yet unique role in my development. My hope is that I go on to represent you in
a way that will make you proud.
A special thank you goes out to my fellow student Evelyn Gladney for lending me your
ear, and giving me your support along the way. Now that I have graduated, I look
forward to shaking your hand when it’s your turn.
To my dearest friend Carol, there are no words to express my gratitude to you for being
there whenever and wherever. You encouraged me from the start and stuck with me as I
went up each hill and through every valley to the very end. Attending the graduation
ceremony and taking the time for a more personal celebration has leﬁ me with fond
memories that will carry me through life.

Funding Source: National Institutes of Health, National Heart Lung & Blood Institute,

Minority Supplement Award: Grant No. ROlH68971, PI: CLM Joseph, PhD

TABLE OF CONTENTS

LIST OF TABLES ......................................................................... vii
LIST OF FIGURES ........................................................................ ix
CHAPTER 1
INTRODUCTION ................................................................. 1
Conceptual Model .......................................................... 11
CHAPTER 2
REVIEW OF THE LITERATURE .............................................. 16
CHAPTER 3
Methodology ............................................................... 42
Research Questions ........................................................ 42
Design ....................................................................... 43
Procedure .................................................................... 46
Measures ...................................................................... 50
Data Analysis ............................................................... 61
CHAPTER 4
RESULTS ................................................................... 65
CHAPTER 5
DISCUSSION ............................................................. 109
Limitations .................................................................. 1 19
Implications ................................................................. 121
APPENDICES
Lung Health Survey ........................................................ 131
Baseline Survey ............................................................. 135
REFERENCES ............................................................................... 163

vi

LIST OF TABLES

Table 1. Characteristics of Collaborating High Schools ................................... 45
Table 2. Summary of Major Study Variables and Their Measurement .............. 56 - 60
Table 3. Demographic Characteristics of Study Population ............................... 67
Table 4. One-Way AN OVA of Study Variables by Gender ............................... 70
Table 5. Means SD and One-Way ANOVA of Study Variables by Diagnosis ......... 71
Table 6. Crosstabulation of Asthma Severity by Diagnosis ................................. 73
Table 7. Crosstabulation of Asthma Severity by Gender ................................. 74
Table 8. One-Way ANOVA of Study Variables by Asthma Severity 76
Table 9. Means and SD of Study Variables by Asthma Severity .......................... 77
Table 10. Means and SD of Overall PES and Subscales .................................... 79
Table 11. Pairwise Comparison of Sources of PBS .......................................... 80

Table 12. Multivariate Analysis of PBS by Gender, Asthma Severity and

Diagnosis ............................................................................... 81
Table 13. Test of Between Subject Effects for PBS by Gender ............................ 82
Table 14. Estimated Marginal Means for PES by Gender .................................. 83
Table 15. Crosstabulation of PASRD by Gender ............................................ 87
Table 16. Crosstabulation of PASRD by Diagnosis .......................................... 88
Table 17. Crosstabulation of PASRD by Asthma Severity .................................. 89
Table 18. Pairwise Comparison of QOL Subscales ......................................... 91
Table 19. Multivariate Analysis of PBS by PASRD ........................................ 93
Table 20. Regression Analysis for the Moderator Effect of PASRD on the Relationship

between PBS and DSM ............................................................. 95
Table 2]. Regression Analysis of PES on Health Outcomes ............................... 96

vii

Table 22. Regression Analysis for the Moderator Effect of DSM on the Relationship
between PBS and Health Outcomes ................................................ 98

Table 23. Regression Analysis for the Moderator Effect of DSM on the Relationship
between PBS and QOL ............................................................. 101

Table 24. Regression Analysis for the Main Effect of PASRD on Health Outcomes 102

Table 25. Regression Analysis for the Mediation Effect of DSM on PASRD and Health
Outcomes ............................................................................ 103

Table 26. Regression Analysis for the Moderator Effect of DSM on the Relationship

between PASRD and Health Outcomes .......................................... 104
Table 27. Regression for the Mediator Effect of DSM on the Relationship between

PASRD and QOL ................................................................... 105
Table 28. Regression Analysis for the Moderator Effect of DSM on the Relationship

between PASRD and QOL ........................................................ 106
Table 29. Hierarchical Regression for Predictors of QOL ................................ 107
Table 30. Hierarchical Regression for Predictors of QOL by Gender ................... 108

viii

LIST OF FIGURES

Figure 1. Conceptual model of hypothesized inﬂuences on disease self-management
and health related outcomes 6

Figure 2. Moderator Model of PES and DSM .............................................. 117

ix

Chapter 1
INTRODUCTION

Urban African American youth with asthma experience disproportionate disease
severity, morbidity and mortality when compared to Caucasian counterparts (American
Lung Association, 2004, McDaniel, Paxson, & Waldfogel, 2006). These disparities exist
at a time when scientiﬁc knowledge of the disease and the availability of effective
treatment options are unprecedented. To date explorations of factors among urban
Aﬁican American adolescents that contribute to these poor health outcomes and quality
of life attributed to asthma have failed to explain these disparities or identify effective
interventions. However, an emerging focus of research targeting youth with a chronic
disease has begun to examine developmentally relevant social contextual variables such
as differing ﬁrnctions of social support, intrapersonal factors such as self-regulation and
their relationship to disease self-management behavior and health outcomes.

The ability of adolescents affected by asthma to successfully implement a prescribed
disease management regimen is a critical element of disease control. Although clinicians
are essential in the diagnosis, planning and education of adolescents with asthma, the
affected individual’s role in the day to day disease management that signiﬁcantly
contributes to health outcomes is unparalleled. Disease self-management behavior
includes symptom monitoring, avoidance of known asthma triggers, medication
administration and adjustment, attack management and prevention and health evaluation
visits. The primary goal of disease self-management behavior is to optimize disease
control. According to the National Heart Lung and Blood Institute’s Expert Panel Report

H (1997) [EPR-II], effective disease self- management behavior would be expected to (a)

prevent asthma symptoms, (b) minimize missed school or work, (c) minimize the need
for emergency department visits and hospitalizations, (d) contribute towards maintenance
of normal activity levels, (e) contribute towards normal or near normal lung function and
(t) to result in minimal or no medication side effects. Effective disease self-management
behavior and optimal disease control would allow youth to achieve the goal of living a
“normal life” and to achieve clinically signiﬁcant levels of health related quality of life.
Living a normal life is described by youth as being similar to peers and being able to
actively participate in routine everyday activities without worry or concern (Rydstrom,
Englund, & Sandman, 1999).

The primary responsibilities of disease self-management behavior are transferred from
parent to youth beginning in childhood without much forethought or support for the
transition of responsibilities (Wade, Islam, Holden Kruszon-Moran, & Mitchell, 1999).
The informal and perhaps erratic transfer of disease management responsibility is marked
by a decline in adherence rates among adolescents to rates of 50 percent or less when
compared to preceding childhood adherence rates (Anderson, Ho, Finkelstein, & Laffel,
1997; Kyngas, & Rissanen, 2001). Disease self-management adherence rates of
adolescents are similar to rates found among adult populations. This ﬁnding allows for
one to conjecture that among persons with a chronic disease, patterns of disease self-
management established early in life are continued throughout life. The potential to
signiﬁcantly alter disease self-management behavior that contributes towards effective
disease control, minimize related morbidity and mortality and improve health related

quality of life has far reaching implications that have yet to be realized.

In addition to the normal developmental impact on emotions, youth with a chronic
disease, may experience emotional despair due to disease burden. In fact the relationships
with persons most inﬂuential in the life of adolescents that are the greatest source of
supportive emotional interchange are potentially also the greatest source of emotional
upheaval. As parents caregivers and other signiﬁcant adults in the life of adolescents take
on a more distal role in disease management conﬂict often arises around the emerging
adolescent’s perspective of disease self-management and the contrast to previously
established norms. Although the etiology of some of the parent-child conﬂict is related to
asthma disease self-management, the broader prevailing context that must also be
considered is adolescent development and the related developmental tasks.

Peer relationships become increasingly important during adolescence. Youth strive to
ﬁnd greater similarities between themselves and their age matched reference groups. Yet
this desire is a source of emotional struggle due to the overt physical symptoms of asthma
(wheeze, cough, and Shortness of breath), activity limitations, and disease management
requirements.

Emotional experiences during adolescence occur in the context of continuous
reciprocal interactions with close personal contacts such as parents, peers and signiﬁcant
others. One basic underlying need of adolescents during this period of transition that
transcends all interpersonal relationships is the need for emotional support (a sense of
feeling loved and valued). Emotional experiences are increasingly being recognized as a
common response to disease and illness and are thought to inﬂuence health, well-being,

and treatment outcomes (DeCoster, 2003). Although emotions are a part of the human

experience that is signiﬁcantly heightened during adolescence, little is known about how
they inﬂuence disease self-management behavior.

During adolescence, cognitive processes such as self-regulation (which drive
behavior) affect the way youth set goals related to disease self-management and
ultimately disease related outcomes. According to Karoly, (1993) self—regulation
addresses the process by which the thoughts and behaviors of an individual are adapted
over time within a dynamic context. In line with the dynamic adaptation of self-
regulation described by Karoly, (1993), Zimmerman, Bonner, Evans, & Mellins (1999)
described a model of sequential phases of asthma self-regulation development in which
these skills emerge in disease self-management behavior. This model is highly relevant to
adolescents and the transitions that youth will undergo as they learn to self-regulate
disease self-management behavior. Asthma self-regulation also explores processes that
go beyond the automatized task of disease self-management (inhaler use when wheezing)
that are characteristic of primitive imitative learning to mechanisms of thought that are
goal directed (attack prevention) and that address disease variability and contextual
factors that contribute towards disease severity.

Investigations of adolescent populations with chronic diseases often do not take into
consideration the developmental transitions that provide an evolving context from which
youth function, the central role of the individual towards achieving optimal health
outcomes, and the inﬂuence of social relationships on thoughts and behavior. Asthma
care is prescribed in the clinical setting; however implementation of disease management
that contributes signiﬁcantly to health outcomes takes place in the social environment. In

order to gain insight into factors that inﬂuence adolescent health outcomes it is critical to

examine factors that are both congruent with normal development and that are relevant to
the youth’s social contextual environment. Both perceived emotional support and asthma
self-regulation are contextual factors that will provide a unique approach to
understanding the signiﬁcance of developmentally relevant inﬂuences on adolescent
disease self-management behavior.

The overall goal of the proposed project is to determine the perception of emotional
support among adolescents with asthma and the relationship with disease self-
management behavior. It is hypothesized that this relationship is explained by asthma
self-regulation. Therefore phase of asthma self-regulation development will be explored
as a mediator of the relationship between perceived emotional support and disease self-
management. Finally the association between disease self-management and indicators of
morbidity in asthma (hospitalizations and emergency department visits), asthma
symptoms and asthma health related quality of life will be tested (Figure 1).

It is critical to understand the determinants of disease self management during
adolescence due to the fact that (a) asthma is a leading chronic disease among urban
minority adolescents, (b) related morbidity is signiﬁcant, (c) youth bear the primary
responsibilities of implementing a disease self- management plan ((1) recognition that
implementation of a self-management plan is key to optimizing health outcomes, and (e)
adolescence is a period when lifelong behaviors can be established.

Trends of asthma prevalence appear to have recently stabilized after a 1997 redesign
of the National Health Interview Survey [NHIS] of asthma prevalence data for the United

States, (MMWR, 2000). However asthma continues to be one of the most

 

 

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common chronic medical conditions in the United States (Michigan Department of
Community Health [MDCH], 2001). More than 30 million Americans reported ever
having had a diagnosis of asthma and 20 million persons reported a current diagnosis of
asthma National Center for Health Statistics [NCHS], 2002).

Persons affected by asthma are plagued by considerable disease related morbidity and
mortality. Although a priority goal of asthma management is attack prevention, in the
year 2002, 12 million persons reported having had an asthma attack in the previous 12
months (NCHS, 2002). Attack rates are a key indicator of uncontrolled asthma.
Uncontrolled asthma results in greater symptom experiences, hospitalizations, emergency
department visits and mortality rates, all of which have continued to increase (Clark et.
a1, 1999; MMWR, 2000; Strunk, Ford & Taggart, 2002). In the year 2002 there were 1.9
million visits to emergency departments for asthma care (N CHS, 2002). Additionally
484,000 hospitalizations were reported for the same year due to asthma. Of great concern
is the fact that persons affected by asthma continue to die despite scientiﬁc gains in
knowledge of disease pathophysiology and related advancements in effective medical
treatment options. Mortality rates for the year 2002 indicated 4,261 persons died from
asthma (NCHS, 2002).

Due to hospitalizations, emergency department visits and other factors that contribute
to the cost of asthma care, national expenditures for the disease are staggering. Asthma is
currently considered an “ambulatory case sensitive condition” which implies that
hospitalizations are preventable with adequate outpatient care (Guendelman, Mead,
Benson, Chen, & Sameuls, 2002). Despite this designation as a case sensitive condition

reports indicate that asthma related direct and indirect health care cost consume 12.7

billion dollars annually. The national expenditure in addition to the high levels of
morbidity, mortality and negative impact on quality of life from asthma collectively and
independently warrants investigations into strategies that can reduce the burden of asthma
and improve health related outcomes.
Asthma in African Americans

Asthma prevalence, morbidity and mortality all demonstrate signiﬁcant disparities by
minority race when compared to non-Hispanic whites. (Litonjua, Carey, Weiss, & Gold,
1999; NCHS, 2002). In the year 2002 asthma prevalence was reported to be 30% higher
among non-Hispanic blacks compared to non-Hispanic whites (NCHS, 2002). The
asthma attack prevalence rate in 2002 among diagnosed Aﬁican Americans was also 30%
higher than rates found among non-Hispanic whites (NCHS, 2002). African Americans
have consistently demonstrated higher emergency department visits and death rates from
asthma than any other ethnic group with current available estimates (American Lung
Association, 2003; MMWR, 1998). Comparative data indicate that African Americans
are 3 times more likely to be hospitalized from asthma and 4 times more likely to die
from asthma when compared to Caucasians (Strunk et a1., 2002).
Asthma in Adolescents

Asthma is a leading cause of chronic illness among youth which continues throughout
the adolescent years. In fact prevalence estimates and asthma attack rates are greater
during adolescence when compared to younger ages. Between 1995 and 1996 youth age
11-17 had greater asthma prevalence estimates than younger age groups (MMWR, 2000).
In 1997 and 1998 asthma attack prevalence rates among this same age group were also

greater than for children age 10 and younger (MMWR, 2000). This pattern of greater

disease morbidity among adolescents is consistent with global trends among youth age
13-14 who report greater symptom experiences (cough, wheeze) than younger age
groups within the past 12 month period of assessment (Braun-Fahrlander et al., 1998). In
the United States morbidity among adolescents is ﬁrrther evidenced by the over 14
million missed school days annually and reported activity restrictions (Clark et al., 1999;
Schleicher, Koziol, & Christiansen, 2000).

Asthma in African American Adolescents

The characteristics of persons considered to be at greatest risk for asthma morbidity
and mortality include living in an urban setting, being of non-Caucasian race, having a
household income consistent with a lower socioeconomic status, and being young
(Schleicher et al, 2000). Asthma in urban African American adolescents is a priority
health concern due to the disproportionate health disparities found in this population.
National estimates of disease prevalence, mortality and morbidity are sparse in that most
reports classify adolescents with children. Collectively data is often reported as children
0-17 years of age. However some state data provides a more detailed record of asthma
health statistics among the adolescent population.

In Michigan 29.9% of non-Hispanic black middle (6th -8th grades) and high school
(9m-12th grades) students have been told in their lifetime that they had asthma compared
to 20.6% of age matched white students (MDCH, 2004). Among this same population
current and lifetime asthma is signiﬁcantly higher for black students than for white
students (MDCH, 2004). Nationally, non-Hispanic blacks had an asthma prevalence of
30% higher than non-Hispanic whites. When assessing asthma control as indicated by

attack prevalence within the previous 12 months non-Hispanic blacks had Asthma

prevalence, morbidity and mortality are higher among urban African American
adolescents than non-Hispanic White age matched peers, (Clark et. a1, 1999; Centers of
Disease Control [CDC], 1996). Results of the National Health Interview Survey (NHIS),
2001, indicate prevalence rates for Non-Hispanic black youth to be 10% higher than non-
Hispanic white and 40% higher than Hispanic youth (combination of all groups of
persons identiﬁed as Hispanic). The disparities of asthma related mortality are further
substantiated in that among persons aged 15-24 with asthma, African Americans were 6
times more likely to die than Caucasians (CDC, 1996). The disparities found among
urban African American adolescents are disturbing and indicate that these youth have yet
to demonstrate a signiﬁcant reduction in disease related morbidity, and mortality. This
population requires further exploration of personal and environmental factors within the
context of normal adolescent development that are central to asthma control and related

health outcomes.

10

Conceptual Model

Self-Regulation: A Social Cognitive Perspective

For years human behavior was thought to be the result of observation based
learning experiences. Little or no consideration was given to internal mediating thought
processes. However more recently scientists have increasingly begun to recognize the
multidimensional mechanisms of human behavior and the previously ignored
relationships between external inﬂuences and internal processes. Behavior is no longer
thought of so simplistically or without signiﬁcant consideration to intrapersonal and the
interpersonal interactions between humans and their environment. In this study an
examination of the relationships between external inﬂuencing factors and internal
cognitive process and the effect on behavior will be conducted guided by self-regulation
theory using a Social Cognitive perspective.

Disease self-management behavior informed by Social Cognitive Theory (SCT), is a
leading theory that has successﬁilly been used as a guide to explain and predict health
behavior among adolescents (Montgomery, 2002). The explanatory focus of the theory
provides direction for scientiﬁc inquiries such as the current investigation that are
attempting to gain insight into the Signiﬁcance of associations of personal inﬂuences
(cognitive or affective factors) environmental inﬂuences ( social or physical factors) and
behavior (actions and reactions of the individual) (Clark & Zimmerman, 1990). The
theory has also demonstrated its predictive qualities that support interventions designed
to facilitate behavior change among persons with a chronic disease (Clark, Valerio,

2003). SCT hypothesizes that relationships between personal inﬂuences, environmental

ll

inﬂuences and behavior constantly interact in a reciprocal deterministic manner
(Bandura, 1989). These interactions are signiﬁcantly inﬂuenced by self-regulation
processes (Clark, & Zimmerman, 1990). Although the model is triadic and there are
several reciprocal inﬂuences on behavior, the sources of inﬂuence differ in terms of
strength of association and the timing of their reciprocity (Bandura, 1986). This can be
interpreted as meaning that competing inﬂuences are not necessarily equal and the
reciprocal nature of inﬂuences is not simultaneous (Bandura, 1986).

Zimmerman uses the theory of SCT to formulate a perspective of understanding the
theory of self-regulation. Self-regulation takes into account the cognitive sub-processes
(self observation, self-judgment and self-evaluation) which guide one’s decisions to
maintain, modify, or discontinue a behavior. The loop of self-regulation is initiated
through the use of behavioral strategies and is subsequently changed based on enacted
feedback (Clark & Zimmerman, 1990). Over time and with support, individuals
increasingly learn to use the evaluative feedback mechanisms of self regulation as a
primary means of regulating behavior. As adolescents mature, evaluative consequences,
increasingly are based on ones own personal standards or goals and less inﬂuenced by
external agents. This change in reliance on external inﬂuences is consistent with the
changes in disease self-management during adolescence where youth begin to set their
own standards as they rely less on the standards of parents. The social cognitive
perspective of self-regulation has been found to play a central role in disease self-
management (Clark, Gong, & Kaciroti, 2001). There are three sub-processes of self-
regulation that are hypothesized as key in the use of disease self management behavior

for asthma.

12

The sub-process of self-observation refers to the active role of monitoring ones own
behavior or the behavior of others towards a speciﬁc related asthma health goal. An
asthmatic perhaps would begin to keep track of the number of times that they have
participated in a selected sport without having to stop the activity due to asthma
symptoms. The observation serves the purpose of providing information for self-
judgrnent regarding a behavioral strategy (use of a new medication) to goals
(uninterrupted sports participation) through the mechanism of conscious awareness. Thus
observation is purposeful in self-regulation as described by Langer, (1989), “it signals
temporary disengagement from automaticity or a transition from mindlessness to
mindfulness”. Self-observation is not limited to attentiveness to one’s own behavior, but
also to the behaviors of others as it applies to one’s goal pursuit. For example persons
with asthma are advised to limit and or avoid direct and indirect exposure to tobacco
smoke. However the adolescent may note the frequency in which their exposure to
tobacco smoke results in subsequent asthma symptoms.

Self-judgment is the use of speciﬁc criteria to assess a given situation or problem
based on ones goals (Clark & Zimmerman, 1990). In the previous example the problem
was active participation in sports resulting in frequent interruptions due to asthma
symptoms such as cough, wheeze or difﬁculty breathing. Self-judgment would entail
judging the effectiveness of a new medication based on personal standard for acceptable
interruptions in sports activities. The youth may set a goal of no interruptions per practice
session. By using the information obtained from self-observation, the youth would
compare and contrast the difference in sports related activity tolerance prior to and after

the initiation of a new medication.

13

Self-reaction/evaluation is the act of purposefully attempting to detect discrepancies
between one’s goals and related strategies by reacting to self-observation and self-
judgment (Clark & Zimmerman, 1990). As the individual reacts they determine the
efﬁcacy for continuing, changing or abandoning a behavior. Continuing with the previous
example the youth may determine from self-observations and self-judgment that use of a
new medication has no observable effects on their ability to participate in sports activities
without frequently occurring asthma symptoms. Their reaction to this ﬁnding could result
in a change in behavior such as discontinuation of the medication or increasing the
dosage or frequency of the medication.

Being self-regulating is key to optimizing disease self-management because ones
behavior is goal oriented, inclusive of self observation/monitoring and self reaction
within a feedback loop. This is in contrast to behaviors that are driven by habit, tradition,
or directives that have little meaning or value to the individual and that have an end point
deﬁned by completing a task. Personal and environmental factors serve to inﬂuence the
sub-processes of self-regulation and the subsequent behavior. What is not known is how
the environmental factor of perceived emotional support inﬂuences asthma self-
regulation. In the current proposal the inﬂuence of an environmental factor (perceived
emotional support) will be examined for the association with phase of asthma self
regulation development and disease self management. Self-regulation is a proactive as
well as reactive process of disease self-management that requires more than knowledge
or initial commitment (Zimmerman et al., 1999). According to SCT the individual and
the context within which they implement a disease self-management regimen is central to

understanding related behavior.

14

Although self-regulation has innate qualities exhibited as early as infancy, throughout
life the process is adaptable to dynamic context (i.e. adolescent development and or
disease self-management) whereby skills are developed over time in what appears to be a
phased sequential path (Zimmerman et. al, 1999). The sequential phase approach of
understanding self-regulation is similar to other theories of behavioral change such as the
Transtheoretical Model of Behavior Change. A sequential phase of self-regulation
accounts for the process of changing underlying beliefs and methods of coping in order to
adopt a preventive asthma regimen (Zimmerman et al., 1999). A SCT perspective of
self-regulation was selected to guide the understanding of how the interaction of an
environmental inﬂuence (perceived emotional support) and a personal inﬂuence (phase of
asthma self-regulation) and behavior (carrying a rescue medication at all times) are
related and to determine the direct and indirect effect of these variables on health related
outcomes and asthma health related quality of life.

Emotions and cognitions such as the processes of self regulation are thought to be
intricately and dynamically linked. Further this interrelationship is also hypothesized as
one of the mechanism by which information is processed and actions executed (Bell, &
Wolfe, 2004). Social Cognitive theory (SCT) was selected as the guiding framework to
examine these relationships because a major thrust of the theory has been to gain an
understanding of how social cognitive variables interact with self-regulating processes to
achieve desirable health behaviors for disease self-management (Zimmerman, 1999).
Further SCT combines the elements of social, cognitive, and developmental psychology

which are consistent with the focus of the current study.

15

Chapter 2
REVIEW OF THE LITERATURE

Disease self-management consists of behaviors that are implemented by persons with
a chronic disease such as asthma in an effort to minimize symptoms, control disease and
improve health outcomes. Factors that inﬂuence disease self-management which
contribute to health outcomes among adolescents are not fully understood. Adolescence
is an opportune time to Optimize disease self-management behavior that may persist
throughout life. The inﬂuence of social contextual factors hypothesized to inﬂuence
disease self-management behavior will be discussed using a Social Cognitive view of
self—regulation which is the selected theoretical model that will be used to guide this
research project. A review of the literature as it applies to the components of the model
proposed for this research will follow.
Gender

Gender refers to the behavioral, cultural or psychological traits (Merriam-Webster
online) that males and females learn via the socialization process. Through the process of
socialization males and females learn interpersonal and interaction skills that are in
conformity with the values of ones’ society (Dictionary.com/socialization). Socialization
usually begins with the family and is further shaped by relatives, friends, and the greater
society at large. For example males are socialized to handle problems independently
while females are encouraged or allowed to express dependency (Barbee et al., 1993).
Female role expectations often emphasize nurturance and emotional expressivity while
male roles emphasize achievement success and inexpressiveness. The socialization

process begins early in life and provides the bases for differences in how males and

16

females interact with others in social relationships, how they may seek support (Barbee et
al., 1993) and potentially how they think about situations that require self-regulation.
These ﬁndings suggest that gender should be examined as a covariate for its potential
inﬂuence on study variables.

Available data for gender also suggest differences in terms of prevalence, morbidity
and mortality rates among youth less than 18 years of age. Males have been found to be
hospitalized at rates 60% higher than females. Within this same population death rates for
males occur at a rate 80% higher that that for females (MDCH, 2005). Among youth
within a Medicaid population, persistent asthma is found 40% more often in males than
females (MDCH, 2005). Data that focused speciﬁcally on adolescents ﬁ'om the Youth
Risk Behavior Survey (CDC, 2003) found that among youth attending high school in
grades 9-12, signiﬁcantly more females than males with a current asthma diagnosis
reported an asthma episode or attack within the most recent 12 months of being surveyed
(CDC, 2005). Speciﬁc data on adolescents in terms of gender differences in mortality
and morbidity is limited due to the common practice of grouping adolescents with
children under the age of 18. This ﬁnder further justiﬁes the inclusion of gender as a
covariate of interest in the current stud to help determine if there are differences among
adolescent youth in the study population.

Diagnosis

Asthma has been reported as an under diagnosed condition among children,
adolescents and young adults (Siersted, Boldsen, Hansen, Mostgaard & Hyldebrandt,
1998; Yeats, Shy, Sotir, Music, & Herget, 2003). In a study of Danish adolescents,

females were found to be overrepresented among youth without a diagnosis of asthma

l7

when compared to diagnosed teens where females are underrepresented (Siersted et al.,
1998). Cough which is a hallmark symptom of bronchitis was found to be a primary
presenting symptom among youth with undiagnosed asthma. This symptom may have
contributed to a repeated diagnosis of bronchitis among adolescents as opposed to a
diagnosis of asthma (Siersted et al., 1998). Further less than one third of adolescents with
undiagnosed asthma reported their symptoms to a doctor (Siersted et al., 1998).
Undiagnosed youth that report asthma symptoms experience signiﬁcant health
consequences (Y eatts, et al., 2003). In a study of youth ages 12-14 in North Carolina,
20% of undiagnosed youth missed a half day or more of school per month due to wheeze
compared to 47% with a diagnosis (Y eatts et al., 2003). Another 25% limited activities
because of wheeze once or more per month and 32% reported sleep disturbances because
of symptoms of wheeze during a 4 week period (Yeatts et al.,2003). The impact of being
undiagnosed is ﬁirther exempliﬁed in these youth who report 1 or more ED visits for
asthma-like symptoms and 5% reporting a symptom related hospitalization in the past
year (Yeatts et al., 2003). Persons with asthma-like symptoms have not been well studied
among urban high school adolescents. Therefore persons that report symptoms consistent
with asthma over the past 12 months will be included in the current study. The study will
also exam how the main study variables differ by diagnosis.
Severity

According to the NHLBI Expert Panel Report 11 (1997) there are 4 severity
classiﬁcations for asthma. These classiﬁcations are based on the individual’s subjective
report of asthma symptoms and or the objective measurement of airway obstruction.

Severity classiﬁcations are; mild intermittent, mild persistent, moderate persistent and

18

severe persistent. In general the greater the frequency of asthma symptom experiences
and or the greater the objective measure of airway obstruction, the greater the asthma
severity.

Asthma severity is an important predictor of health outcomes and asthma health
related quality of life. Among adolescents with mild asthma that participated in high
school sports from a suburban school in Western Washington, health related quality of
life was found to be Signiﬁcantly lower when compared to their healthy peers (Hallstrand,
Curtis, Aitken, & Sullivan, 2003). Similar ﬁndings were noted in a study of primarily
Aﬁican American children between the ages of 5-12 from the Atlanta Empowerment
Zone. Results from this study found that health related quality of life was negatively
correlated with asthma severity, and missed school days.

Although the relationship between asthma severity, and health outcomes has been
studied among youth results have not been found to be signiﬁcant. Munzenberger, &
Vinuya (2002) implemented an intervention study of primarily African American
children age 7-13. Although they were able to demonstrate signiﬁcant improvements in
asthma severity (measured by symptom experiences) no signiﬁcant association was found
between asthma severity and quality of life. The ﬁndings by Munzenberger and Vinuya
(2002) are similar to results of a school based intervention developed for inner-city
school children ages 8-13. In the school based study results demonstrated signiﬁcant
improvements in self-care measures, however, there were no signiﬁcant differences
between the control and intervention group on the health outcomes urgent visits to the

doctor or school absenteeism.

19

Although the studies discussed did not demonstrate an association between asthma
severity and the health outcomes described, none focused on urban teens in high school.
It is important to determine if ﬁndings among adolescents will be similar to those among
younger youth. An understanding of the factors that are associated with health outcomes
such as hospitalizations and emergency department visits among adolescents has
important implications. If severity is not associated with factors such as health-related
quality of life, hospitalizations and emergency department visits, it will be important to
study this population further to better understand what aspects of their disease are related
to outcomes of interest to the affected individual and to clinicians.

In the studies reviewed, evidence suggests that greater asthma severity is not
associated with health related quality of life. Health related quality of life has been
described as an important health outcome that has signiﬁcance to the daily life of the
affected individual. Evidence of the magnitude of disease severity among adolescents
was demonstrated in the ﬁnding that youth classiﬁed in the lowest severity rating (mild
intermittent) were found to have a signiﬁcantly poorer health related quality of life than
their disease free counterparts. To this end, severity will be used as a covariate to
examine differences among youth in the current study. By using severity as a covariate
this investigation will be able to examine the signiﬁcance of how symptom experiences
as compared to diagnosis status is related to health outcomes.

Perceived Emotional Support

Perceived emotional support will be operationalized in this study as the individual’s

perception of being loved and valued by family, friends and special persons in this study.

As youth begin to exert greater independence in thought and behavior around disease

20

self-management, it is critical that close personal contacts of adolescents continue to
display love and support despite predictable inadequacies and uncertainties. Taking a
developmental perspective to address disease self-management is a key to understanding
factors that inﬂuence health outcomes, reducing asthma morbidity and mortality and
improving health related quality of life.

Much of the evidence relating the social support and disease self-management and or
disease control is derived from the correlation of various functions of social support
(instrumental, informational, emotional, appraisal) and speciﬁc disease self-management
behaviors that contribute to health outcomes. Studies that included emotional support in
general also included other support functions. The following review will discuss ﬁndings
related to emotional support and other support functions concluding with the relevance to
the current study.

Social support and disease self-management behavior during adolescence has
primarily been studied among diabetic populations. The disease self management
requirements for adolescents diagnosed with diabetes and asthma are similar in that both
require daily medication, self-monitoring, adaptation of a medical regimen to changing
levels of physical functioning, and other dynamic individual and social contextual
variations. Diabetes is also a common disease among adolescents. The following review
of literature related to social support and disease self-management behavior will focus on
adolescents with asthma and diabetes that addresses self -management and or disease
related health outcomes.

Recently Sin, Kang, & Weaver (2005) examined the relationships between asthma

knowledge, self-management and social support among urban African American

21

adolescents with asthma. The social support functions examined in the study were total
ﬁmctional support (combination of affect, afﬁrmation, and aid), network support (number
of person in network, duration of relationships and frequency of contact) and total loss
(combination of number of persons lost and amount of support lost reﬂecting support no
longer available). In the above study, asthma knowledge and social support were found to
be predictive of self-management behavior. Parents, friends, and school teachers (in this
order) were the most commonly identiﬁed sources of support for youth with asthma.
Parents, when compared to other sources of support most often, provided various forms
of aid support (money or a ride to the doctor). Total support was positively correlated
with asthma knowledge r = 0.31, p<0.05 as well as asthma self-management behavior

r = 0.34, p< 0.008. The overall model testing showed that asthma knowledge and social
support accounted for 14% of the self-management behavior variability (F= 4.05,

p = 0.024 (Sin et al., 2005).

Findings from the above study provide evidence for the relationship between social
support and self-management behavior among African American adolescents. However
the support functions tested did not include emotional support which had it been included
may have added to the variance explained by the model. Further it is not clear if any
speciﬁc support ﬁmction or source of support contributed more to the relationship
between social support and self-management behavior. Another concern brought forth in
the study was the ﬁnding that when adolescents were asked if they sought support during
an asthma attack, 23% indicated that they never seek help from other people at the ﬁrst
Sign of breathing problems (Sin et al., 2005). This is unfortunate in that management of

early asthma symptoms can prevent debilitating exacerbations that result in emergency

22

department visits and hospitalizations. Of question is the reason that adolescents do not
seek support and if provisions of emotional support would inﬂuence this critical choice
during independent decision-making.

In a study of 266 Finnish adolescents with asthma, Kyngas (1999) studied social
support and other factors that predicted compliance with a medical regimen. Only results
that pertain to social support will be discussed. Compliance was measured by self report
that was later analyzed to form three levels of compliance; good, satisfactory and poor. In
this study social support function was not clariﬁed, but source of support was identiﬁed
as parent, physicians, and nurses. Results indicated that of adolescents with good
compliance reported receiving support from parents (93%), physicians, (99%) and nurses
(98%). These ﬁndings are in contrast to youth that reported satisfactory compliance and
received support from their parent (7%), physician (1%) and nurses (2%). Adolescents
that rated themselves as having poor compliance did not report receiving support from
parents, physicians, or nurses.

Subsequent to the above analysis Kyngas, & Rissanen, (2001) added near equal
numbers of adolescents with epilepsy, juvenile rheumatoid arthritis, and insulin-
dependent diabetes mellitus to the sample. Each group of youth answered the same
questionnaire that was tailored to the speciﬁc disease. An additional source of support
(friends) was included. The results using odds ratio indicated that social support from
nurses when compared to social support from physicians, family, and friends was more
predictive of compliance with health regimens by adolescents OR = 7.28, p < 0.0000,

3.42 p = 0.09, 2.69, p = 0.07 2.11, p = 0.67 respectively.

23

There are several notable limitations in the studies of adolescents with asthma and
social support. First only total scale scores for social support were reported. It was not
clear if any speciﬁc support function contributed more to disease self-management than
another. It is also unclear which functions of social support were measured. Although
nurses were considered an important source of support, it is not clear which support
function provided by nurses contributes most to compliance with a medical regimen. Due
to the fact that relationships between support functions and disease self-management
vary, it is important to clearly identify the support function under investigation.
Clariﬁcation of these relationships will allow investigators to determine interventions that
target sources and functions of support that contribute most to disease self-management
behavior.

Multiple studies have been conducted among adolescents with diabetes to examine the
relationship between family and peer support, self-management and serum markers of
disease control such as hemoglobin A1c(HbA1c). The type of support functions varied
within studies with most measuring several functions such as instrumental, informational,
emotional, and appraisal support. In some reports the different ﬁmctions of support were
not always deﬁned making comparisons between studies difﬁcult.

The demographic characteristics of study populations have primarily been adolescents
ranging in age from 10-18, Caucasian race, and middle to upper income socioeconomic
status (Greco et al., 2001; Hanna & Guthrie, 2001; LaGreca & Bearman, 2002; Schroff
Pendley et al., 2002) Skinner & Hampson, 1998). In studies where age varied enough,

comparisons were made between older and younger youth. In all studies except one,

24

older adolescents perceived less support than younger participants (LaGreca & Bearman,
2002; Skinner & Hampson, 1998).

Families consistently provided more instrumental support than friends in the form of
giving insulin injections, blood glucose testing, and preparing meals (La Greca et al.,
1995; LaGreca & Bearman; Skinner & Hampson, 1998). These tasks are consistent with
qualitative ﬁndings from focus group interviews of adolescents conducted by Hanna &
Guthrie (2001) where youth described assistance with tasks as helpful supportive
behavior. Instrumental support for diabetes task were often associated with better
compliance and better HbA1c levels which is considered an indicator of metabolic
control. It is clear that as youth age they are given less support for the task associated
with disease self-management, but what is not known is what type of support is
consistent with the transference of responsibilities for disease related tasks including the
related cognitive processes of self-observing, self-judging and self-evaluating these
events.

Peers are an important source of support for adolescents. As adolescents begin to
spend more time with peers and attempt to identify with age matched referents it is
unclear how support within the relationship is associated with disease self-management.
Peers are often found to provide higher levels of disease speciﬁc and global emotional
support than families among youth with diabetes, however this support has not been
found to correlate with self-management activities (except diet) or metabolic control (La
Greca et al., 1995; Shroff— Pendley et al., 2002). Further exploration of this relationship is

needed as proposed by the current study to determine if these ﬁndings hold true among

25

urban adolescents with asthma and if other factors such as self-regulation may interact
with emotional support and disease self-management.

Based on review of the social support literature, few studies focused on adolescents
with asthma and emotional support. In fact urban African American adolescents and
youth from lower socioeconomic groups that are at high risk for negative health
outcomes related to a chronic disease were a part of only one study population. These
ﬁndings support the focus of the current study population and the need to describe
emotional support from parents’, peers and special persons within this understudied
population. Also a concern raised from the literature review is the ﬁnding that
adolescents often report lower levels of emotional support from parents when compared
to friends. Parents are critical to successful adolescent development. Youth with a chronic
disease may struggle with moving towards autonomy in disease self-management if
emotional support is not available.

Finally although each study identiﬁed examined relationships between social support
and disease self-management tasks, none evaluated the relationship between social
support and self-regulation. In the current study self-regulation development is
hypothesized to be an important variable that may account for the differences in disease
self-management among adolescents. An understanding of the relationship between self-
regulation and disease self-management may further explain the variances found in the
study by Sin et a1. (2005) which only explained 14% of the variability in self-

management behaviors.

26

Self-Regulation

Adolescents diagnosed with asthma rarely focus on long-term disease control. Routine
activities of the adolescent are generally associated with an immediate gain such as
pufﬁng on an inhaler during an acute asthma attack to relieve symptoms. Although this
behavior is consistent with attack management, it does not contribute to disease control.
Additionally this action generally takes place when symptoms become severe, and if the
inhaler is readily available. Actions that must be taken in advance to prepare for an attack
(carrying a rescue inhaler) that may occur outside of the window of immediacy pose a
potential disconnect to adolescents. In order to become effective managers of their
disease, youth must learn to set Short term and long term goals and to implement the
related activities in a multitude of settings and social situations. Adolescents who are able
to self-regulate disease self-management behaviors are expected to ultimately have better
health outcomes than persons who rely on acute severe symptom experiences to drive
behavior (Clark, et al. 2001).

Self-regulation offers a means of focusing asthma disease self-management behavior
around goals consistent with disease control (Zimmerman et al., 1999). Self-regulation is
also consistent with the developing adolescents’ desire for autonomy and identity
formation as disease manager. The ability to self-regulate however is not fully innate, but
is progressively developed through social modeling, support and feedback that are
gradually withdrawn over time as the individual becomes adept at goal setting and the
process of goal attainment (Clark & Zimmerman, 1990). The increasing ability to self-

regulate is consistent with adolescent cognitive development which allows youth to more

27

rapidly acquire knowledge; process information, problem solve and reﬂect on outcomes
(Bruzzese et al., 2004).

According to Zirnrneran et al., (1999), self regulation development is sequential.
Among asthmatics four stages of have been identiﬁed: (Phase 1) Asthma symptom
avoidance; (Phase 2) Asthma acceptance; (Phase 3) Asthma compliance; and (Phase 4)
Asthma self-regulation. Among adult caregivers of children with asthma, phase of self-
regulation has been found to be related to asthma symptoms such as wheezing, sleep
disturbances, activity restrictions and emergency department use. Zimmerman et a1.
(1999) found that higher phase of self-regulation was associated with fewer days of
wheezing, sleep disturbances, home restrictions and emergency department visits.
Additionally self-efﬁcacy, management/prevention behaviors and resourcefulness
increased with higher phase of self-regulation. The cognitive changes that occur during
adolescence may best be represented by a phased approach to describing self-regulation
within this population.

The sub-processes of self-regulation have also been examined among caregivers of
children with asthma for associations with disease management (Clark , Evans,
Zimmerman, Levison, & Mellins. 1994; Clark, et al., 2001). In the ﬁrst study by Clark et
al., (1994) parental asthma self-regulation was found to account for 10% of the variance
in mother’s asthma management behavior and 12 % of the variance in preventive
behavior for asthma. In a second study by Clark et al., (2001) self- regulation was
measured over a 22 month period (baseline, 6 months and 1 year, and 2 years) for the
associations with outcomes (ED visits, hospitalizations, parental report of the child’s

quality of life, parental and ofﬁce visits for follow up asthma episodes. Demographic

28

variables of age, ethnicity, and income proved non-signiﬁcant in this study. The self-
regulation sub-process of making judgments was found to correlate with parental efforts
to observe the child in relevant situations. Making observations consistently correlated
with using more asthma management strategies. The higher the parent’s baseline score
for observing the child in asthma related situations the higher the parental report of the
child’s quality of life score at 2 years There were also signiﬁcant associations between
judgment and use of management strategies. Judgment at baseline was marginally
predictive of physician visits. Management strategies at baseline did not predict outcomes
2 years later.

Findings from the studies described in this review show support for the relevance of
self-regulation to disease self-management and health outcomes. Conclusions about self-
regulation among adolescent populations cannot be drawn from the above studies
however due to the study population being representative of parents and caregivers.
Adolescents are expected to differ from caregivers because of their stage of development
and experience as the manager of a chronic disease. Evidence is needed to determine the
role of self-regulation among adolescents in order to recognize their increasing role in
disease self-management. In this study the phase of self-regulation development will be
examined with the intent to develop appropriate phase based strategies to support self-
regulation in ﬁrture research endeavors.

According to social cognitive theory, children learn self-regulation through external
social means including parental modeling and or assistance (Clark & Zimmerman, 1990).
Further when considering the triadic interacting inﬂuences of behavior, environmental,

and personal factors, each are considered as potentially equally powerful inﬂuences on

29

the development of self-regulation (Clark & Zimmerman, 1990). During adolescence the
primary environmental inﬂuences are family, peers, and potentially other close personal
contacts.

There were no studies found that explored the proposed relationship between any
function of social support and self-regulations in disease self-management. During
adolescence it is important to determine if perceived emotional support that addresses
social contextual developmental needs of youth is associated with self-regulation.
Disease Self-Management Behavior

A primary contributing factor to the negative health outcomes of asthma is ineffective
disease self- management (Kyngas, 1999). Factors that inﬂuence disease self-
management and subsequent morbidity, mortality and quality of life are complex and not
well understood. Yet ineffective disease self-management is known to contribute towards
underlying physiological mechanisms of asthma that result in airway remodeling,
symptom experiences, and ultimately impose functional limitations.

Disease self-management behaviors include the day-to-day activities that youth must
implement such as symptom assessment and monitoring, medication administration and
adjustment, anticipation and management of environmental triggers that contribute to
asthma exacerbations. During the adolescent years self-management behavior is known
to signiﬁcantly decline to rates of ﬁfty percent or less when compared to self-
management behavior in childhood (Anderson, et al., 1997; Kyngas, Rissanen, 2001;
Wade et. a1, 1999). If one were to compare self-management behavior of adults and
youth, one could conjecture that based on reported adult adherence rates, that there is

relatively no change in self-management behaviors from adolescence through adulthood.

30

- It is critical to understand the determinants of disease self management during
adolescence due to the fact that (a) asthma continues to be a highly prevalent disease
among adolescents, (b) related morbidity is signiﬁcant, (c) youth bear the primary
responsibilities of implementing a disease related self management plan ((1) recognition
that implementation of a self-management plan is key to optimizing health outcomes, and
(e) adolescence is a period when lifelong health related behaviors can be established
(NHIS, 2003; Ozer, et al., 2003; Wade et al., 1999).

Asthma drug therapy is a central treatment strategy for disease self-management
among youth. Adolescents also report the desire for complete responsibility for taking
their medications despite admitting the need for support (Slack & Brookes, 1995). In this
study disease self-management will be operationalized as carrying a rescue inhaler.

The focus on rescue medications as opposed to controller medications in this study
was decided upon for several reasons. Although corticosteroids are essential to asthma
control, they have been found to be prescribed less in minority inner city socially
disadvantaged populations (Adams, Fuhbriggee, Guilbert, Lozano, & Martinez, 2002;
Eggleston, et al., 1998). The lack of a controller medication could potentially confound
ﬁndings due to the fact that there were no questions in the baseline survey that would
allow for the interpretation of a negative response regarding following a doctors orders
for controller medication use. However, most inner city adolescents with asthma report
having a rescue inhaler. Use of a rescue medication requires that youth use self-regulation
processes to be prepared for acute attack management and to prevent attack such as those

that result from exercise induced asthma. Therefore although use of rescue medications is

31

not intended for control of disease severity it is an important treatment strategy for
disease management.

Use of a rescue medication by adolescents is poor. Cohen, Franco, Motlow, Reznik, &
Ozuah., (2004) found that among urban African American and Latino youth only 38%
reported taking their “asthma pump” with them when leaving home. This ﬁnding is
consistent with other researchers who have found that teens thought that carrying an
inhaler with them was a bother (Slack & Brooks, 1995) and some reported that using an
inhaler in public places was embarrassing (Penza- Clyve, Mansell, & McQuaid, 2004;
Slack & Brooks, 1995). Another 29% of adolescents reported feelings of embarrassment
by their symptom experiences from asthma and 32% were embarrassed by taking asthma
medicine in front of friends (Cohen et al., 2003). The relationship between
embarrassment of asthma and taking asthma medication raised even more concern in that
youth that were embarrassed about their asthma were less likely to carry their asthma
medications at all times (1:0.98, p<0.001 (Cohen,et al., 2003).

Teens with asthma have identiﬁed that a major goal in their life is to be “normal”
Velsor-Friedrich, et al., 2004). Because of this overwhelming need for normalcy teens are
willing to delay treatment such as taking a rescue medication during an acute attack, even
if it means jeopardizing their health (V elsor-F riedrich, Vlasses, Moberley, & Coover,
2004). Youth participating in focus group studies reveal that they often delay taking
action at the ﬁrst sign of an asthma attack. Instead of immediately attempting to mitigate
symptoms they often wait until symptoms are severe (van Es et al., 1998; Velsor-
Friedrich, 2004) or they just wait out the symptoms until they abate (Raherison, Tunon

De Lara, Vemejoux, Taytard, 2000). Sin et al. (2005) reported that only 49% of

32

adolescents took action when they ﬁrst note breathing problems. Despite awareness by
youth that use of a rescue medication could prevent the onset of symptoms resulting from
exercise induced asthma, few reported taking this preventive action (van Es et al., 1998).
The above behaviors provide evidence of inadequate self-management behavior that
could result in delayed treatment and contribute to hospitalizations and emergency
department visits. According to Milgrom et al., (1995) hospitalizations for asthma could
virtually be eliminated with effective asthma management.

In a study of African American adolescents in an urban city, researchers examined
adolescents self report of disease self-management using the Revised Asthma Problem
Behavior Checklist (RAPBC) (Walders, Drotar, & Kercsmar, 2000). The RAPBC is used
to identify problematic illness management behaviors such as medication usage,
preventive behaviors, and attack intervention strategies (Walders et al., 2000). Findings
indicated that youth reported a mean level of nonadherence of 1.79 (SD 1.5) which
corresponds with “rarely” engaging in problematic illness management behaviors
(W alders, et al., 2000). The ﬁndings above are in contrast to younger children ages 11-
14. Homer (1999) found that middle school children could describe a sequence of
problem-solving steps when faced with an asthma attack. One of the ﬁrst strategies
children used was to self-medicate with an inhaler which they “kept everywhere” such as
school, backpack, or in a locker. Next students evaluated the effectiveness of the
medication and the need for a subsequent dose or the use of a different medication.
Children also described behavioral strategies that included altering their activities during
an asthma attack. Some children even reported taking preventive steps prior to exercise

by self-medications.

33

The evidence of ineffective disease self-management in adolescents is astounding. It is
unclear however what factors inﬂuence disease self-management and why adolescents
demonstrate poorer skills than children. Many studies of disease self-management in
asthma have focused on the use of controller medications. The current study will focus on
the preventive strategy of disease self-management consisting of carrying a rescue
inhaler. In this study perceived emotional support mediated by phase of asthma self-
regulation is hypothesized to inﬂuence disease self-management. Perceived emotional
support is also thought to highlight autonomy which is consistent with the transition
towards independence in disease self-management during adolescence.

Asthma Health Related Quality of Life

Asthma Health Related Quality of Life has become an increasingly important patient
centered outcome measure for persons affected by pulmonary diseases such as asthma
(Hallstrand, et al., 2003). For years clinicians considered subjective assessments of
asthma symptoms and objective measures of airway obstruction as a comprehensive
assessment of the impact of asthma on the individual (Juniper et al., 1996). However,
more recently it has become clear that these measures do not consistency correlate with
the personal impact of the disease that affects one’s day to day functioning (Juniper, et
al., 1996). In addition to the symptom experiences of asthma, adolescents are troubled by
the disease impact on physical, social, educational and emotional ﬁmctioning (Juniper, et
al., 1996). In this study QOL will be operationalized by questions that address activity
limitations, emotional functioning and symptoms related to the impact of asthma on daily

functioning.

34

Few studies have evaluated Asthma Health Related Quality of Life in a consistent
manner among adolescents and even fewer have focused on urban dwelling Aﬁican
American adolescents with asthma. The majority of studies have focused on children
mean age 10-12, and caregivers of children with asthma ﬁ'om racial and ethnic groups
that included few or no African Americans (Graham, Blaiss, Bayliss, Espindle, & Ware,
2000; Sawyer et a1. 2001, Williams et al., 2000). Quality of life has also been measured
using both disease speciﬁc and generic instruments making it difﬁcult to compare
outcomes and even more difﬁcult to interpret results. Studies of children 18 years of age
and younger with asthma where generic or disease speciﬁc quality of life measures have
been used will be discussed.

In studies that included children with asthma QOL has been found to be lower when
compared to disease free controls (Hallstrand et al., 2003). Health related quality of life
has been measured using disease speciﬁc instruments (Erickson etal., 2002; Gibson,
Shah, & Mamoon, 1998; Munzenberger & Vinuya, 2002; generic instruments (Hallstrand
et al., 2003), or in some cases both (Graham,et al., 2000; Sawyer et al., 2001). When
generic instruments were used the study sought to compare children affected by asthma
with healthy counterparts (Hallstrand et al., 2003) When both generic and disease speciﬁc
instruments were used researchers were attempting to determine which factors of quality
of life correlated most with asthma. The instrument used most often among pediatric
population has been the Pediatric Asthma Quality of Life Questionnaire developed by
Elizabeth Juniper, (1996) which is the instrument that will be used in the current study.

In an attempt to determine the impact of asthma on the daily functioning of

adolescents, investigators have sought to determine what factors are associated with

35

health related quality of life. Several investigators deveIOped intervention studies that
focused on improving asthma knowledge as a means of improving health related quality
of life. However, asthma knowledge has not been found to be associated with disease
speciﬁc quality of life (Gibson et al., 1998; Gibson, Henry, Vimpani, & Halliday, 1995;
Munzenberger, & Vinuya, 2002). This ﬁnding does not indicate that knowledge is not an
important variable to consider among youth with asthma, but that knowledge alone is
insufﬁcient to fully understand health related quality of life. Investigators who focused on
symptoms as a predictor of health related quality of life produced inconsistent ﬁndings
among children. Munzenberger & Vinuya, (2002) found no relationship between asthma
symptoms and disease speciﬁc quality of life. However, for adolescents experiencing
dyspnea during exercise, generic quality of life was found to be 4.4 points lower in
adolescent athletes affected by asthma than those not affected by asthma (p=0.02).

Asthma severity and sociodemographic variables have also been investigated as
predictors of health related quality of life. When quality of life was measured using a
generic instrument it was found to be signiﬁcantly lower in children with moderate to
severe asthma (Graham et al., 2000; Sawyer et al., 2001). Of sociodemographic variables
measured, household income was the strongest most consistent statistically signiﬁcant
predictor of disease speciﬁc asthma quality of life (Erickson et al., 2002) Other
sociodemographic variables such as number of siblings were related to symptom
subscales of quality of life but no other sociodemographic variables were associated with
total scale scores (Erickson etal., 2002).

Another focus of QOL research has been on the evaluation of measures of quality of

life including integrative reviews, instrument development and psychometric testing

36

(Eiser & Morse 2001; Rutshauser, Sawyer, & Bowes, 1998; Ruthshauser et al., 2001;
Spieth & Harris, 1995). In theses studies instruments have been tested primarily among
Caucasian, European, and Australian populations. No instruments were speciﬁcally tested
among Aﬁican American adolescents with asthma.

Findings from studies of health related quality of life have yet to demonstrate
consistent ﬁndings among predictor variables. None were found that sought to determine
the association of asthma health related quality of life among urban African American
adolescents or disease self-management. In the current model for this study AQOL is
considered as an outcome variable of disease self-management. It is hypothesized that
better disease self-management will be positively associated with AQOL. This study will
add to the scientiﬁc literature by describing asthma health related quality of life (AQOL)
among urban African American adolescents, and by examining the relationship between
AQOL and disease self-management.

Health Outcomes

Three major categories of outcomes targeted in health care research are (a)
physiologic changes that indicate improvement or lack of improvement in the medical
condition, (b) utilization of resources that incur cost or that negatively affect productivity,
and (c) measures of quality of life and satisfaction with medical care (Blaiss, 2001). In
the current study the adolescent’s report of the frequency of asthma symptoms such as
cough, and wheeze and nighttime awakenings over the past 30 days will serve as
indicators of health care outcomes that target improvement in the medical condition.

Utilization of resources that incur cost will be measured as frequency of hospitalizations,

37

and emergency department visits over the past year. Quality of life as previously
discussed will also be measured as an outcome.

The frequency of symptom experiences by asthmatics serves as a proxy of disease
severity and as indicators of the personal impact of the disease. Asthma symptoms are
most bothersome to adolescents because they often represent the unpredictability of the
disease and they interfere with feeling normal or similar to disease free peers (Callery,
Milnes, Verduyn & Couriel, 2003; Velsor-Freidrich, 2004). Because of the overt nature
of asthma symptoms youth report embarrassment and a sense of no longer feeling similar
to disease free peers (Callery etal., 2003; van Es, et al., 1998). Additionally when
adolescents attempt to alert others such as teachers, or coaches of their symptom
experiences they are faced with disbelief, by the person from whom they may be seeking
help (Velsor-Friedrich, 2004). Youth report feeling that they must prove that the
symptoms are indeed occurring, that they are bothersome, and that they warrant a change
in or discontinuance of an activity. Because of the signiﬁcant impact of the symptom
experiences of asthma, investigators must seek opportunities to impact this negative
health outcome.

Health outcomes identiﬁed as evidence of resource utilization include hospitalizations
and emergency department visits. Among persons age 15 and younger, asthma is the third
ranking cause of hospitalizations (CDC, 2005). In the U. S. the estimated cost of treating
asthma in persons less than 18 is $3.2 billion annually (CDC, 2004). A considerable
factor in the annual cost of asthma care is due to hospitalizations and emergency

department visits (Smith et al.1997; Weiss, Gergen, & Hodgson, 1992) that not only

38

represent a lack of disease control, but also represent a signiﬁcant source of controllable
health expenditures associated with asthma care.

The economic and personal cost of asthma is astounding when one considers the
designation of asthma as a case sensitive condition where hospitalizations could be
prevented. Further it is not clear if the frequency of emergency department visits is
primarily due to a lack of access to medical care in ambulatory clinics, ineffective asthma
care by clinicians, poor self-management skills by the affected individual or due to the
highly unpredictable nature of asthma in which acute attacks may be more common in
some persons than others. In the current project the focus will be on disease self-
management as a predictor of hospitalizations and emergency department visits. Despite
the complexity of factors that may contribute to high resource utilization, disease self-
management holds promise as a means of changing current trends.

Disease self-management is hypothesized to minimize resource utilization. However it
remains unclear as to which disease self-management behavior correlate best with health
outcomes. In a quasi experimental study of Aﬁican American children ages 8-13
(m=10.06 years) Velsor—Friedrich, Pigott, & Srof (2005) examined the effects of a
school-based asthma intervention program on self-care practices, and health outcomes.
Although their intervention demonstrated signiﬁcant improvement in self-care practices
among youth, no signiﬁcant changes were noted in urgent care visits or symptom
frequency.

The ﬁndings in the study by Velsor-Friedrich et al., (2005) differ from those of a
randomized control trial conducted by Guendelrnan et a1. (2002). The age range of the

study population was slightly older was 8-16, m=12.1. Approximately 50% were Aﬁican

39

American, 15% Caucasian and 20% other, in contrast to the previous study sample that
was totally African American. The intervention objective was to assess the effectiveness
of an interactive intemet based asthma monitoring program as compared to the use of a
standard asthma diary. At the 6 week follow up, children randomized to the intervention
group reported fewer activity limitations and signiﬁcantly fewer peak ﬂow readings
(objective indicator of asthma severity) in the yellow zone (caution) or the red zone
(medical alert). At the 12 week follow up, children in the intervention group showed a
signiﬁcant difference in self-care behaviors such as taking asthma medications without
reminders p=0.001 and these behaviors were signiﬁcantly correlated with asthma
outcomes. During the 90 day trial period the daily compliance rates declined as time
progressed for both groups. However control group compliance declined faster than the
intervention group.

The two studies reviewed are similar to others where outcomes vary depending on
study population, type of study, variables, and timefrarnes. No Studies were found that
used the same predictor variables as in the model in the current study. The current study
will focus on an age range of adolescents that should capture middle and older
adolescents. Middle and older adolescents have rarely been targeted in the study of
asthma.

Literature Review Summary

Based on this review of literature of adolescents with asthma, it is apparent that the
factors that contribute most to disease self-management among urban African American
adolescents are not clear. The current study will help to ﬁll this void in the literature by

focusing on the inﬂuence of the social contextual variable emotional support from family

40

ﬁiends and special persons. Although social support is often identiﬁed as important to
adolescents with asthma the speciﬁc support ﬁmction that contributes most to disease
self-management and health outcomes among adolescents is not known.

Additionally a higher phase of self-regulation development by parents of children with
asthma has been shown to positively affect the health outcomes of the children
(Zimmerman et al., 1999). However, evidence is lacking to determine if this holds true
among adolescents as they increase their responsibility for their own disease self-
management. Based on the literature review, both emotional support and asthma self-
regulation development independently have relevance as factors that may positively
inﬂuence health behavior. The current proposal will describe each construct within the
study populations and also examine associations between variables that are hypothesized

to predict disease self-management behavior and inﬂuence positive health outcomes.

41

Chapter 3
METHODOLOGY
The aim of this study was to determine if perceived emotional support is associated
with disease self-management behavior health outcomes and asthma health related
quality of life among urban adolescents with asthma. Self-regulation was considered to
be a potential mediating factor to the relationship between perceived emotional support
and disease self management and health outcomes. Gender, diagnosis of asthma or
symptoms consistent with asthma and asthma severity were considered as covariates
within the model. The proposed study is unique in that the focus is on urban adolescents
with asthma which is a population that has not been studied widely. Also perceived
emotional support and phase of asthma self-regulation development have not been
studied independently or together to determine their relationship with disease self-
management, health outcomes or asthma health related quality of life.
Research Questions
The following research questions were developed to achieve the objectives of this

study: Among urban African American Adolescents with Asthma:

1. What is the perception of emotional support among urban adolescents with

asthma?

2. Does PES differ by gender, diagnosis, or asthma severity?

3. Does Phase of Asthma Self-Regulation Development (PASRD) differ by

gender, diagnosis or asthma severity?
4. What is the relationship between PES and PASRD?

5. What is the relationship between PBS and Disease Self-Management Behavior?

42

6. What is the relationship between PASRD and Disease Self-Management?
Behavior?
7. What is the effect of PASRD on the relationship between PBS and Disease
Self-Management Behavior?
8. What is the effect of Disease Self-Management Behavior on the relationship
between PES and Health Outcomes?
9. What is the effect of Disease Self-Management Behavior on the relationship
between PBS and Asthma Health Related Quality of Life?
10. What is the effect of Disease Self-Management Behavior on the relationship
between PASRD and Health Outcomes?
11. What is the effect of Disease Self-Management Behavior on the relationship

between PASRD and Asthma Health Related Quality of Life?

This study is a secondary analysis of a subset of baseline data, from a randomized

effectiveness trial to evaluate a tailored computerized asthma education and disease

management program (Puff City) for teens. A cross sectional design was used to collect

data to describe the study population and the variables of interest as well as to test a

model of associations between the selected variables, indicators of morbidity and

pediatric asthma health related quality of life.

Students enrolled in grades nine through eleven attending any of the six participating

high schools in Detroit were recruited. Twelfth grade students were not recruited due to

43

their impending graduation which would impact their availability for the intervention and
follow up phase of the parent study. The parent study (Tailored Asthma Management for
Urban Teenagers ROlH68971, PI: CLM Joseph, PhD) is a NIH funded randomized
effectiveness trial. Students with or without a diagnosis of asthma conﬁrmed by a
healthcare provider and or exhibiting persistent asthma symptoms according to EPR- II
(1997) were eligible for the study

Students in the selected high schools all reside in an urban area. At least 52% of the
student households represented qualify for subsidized lunch programs. Zip codes for the
selected high schools are representative of areas with greater socioeconomic
disadvantages including fewer health care resources. According to the 2000 census 15-
50% of children less than 18 years of age residing in the zip codes of the identiﬁed
schools meet federal guidelines for poverty. Selected descriptive characteristics of
students attending participating schools are shown in Table 1. Estimates of potential
affected students was derived from previous ﬁeld work with similar schools in the Detroit
area that yielded a rate of 11% of the student population as having uncontrolled asthma
and approximately 9% having symptoms consistent with asthma without a diagnosis.
Setting

The study took place in six Detroit area public high schools, Cody, Redford,
Mackenzie, Mumford, Northwestern, and Ford. All students completed the screening
survey in a regularly scheduled class (English) and subsequently the baseline survey on a
school computer. The locations of the computers were pre-deterrnined during
collaboration with school staff at each respective school. Factors taken into consideration

regarding placement of the computers included, availability of network connections,

44

Table 1

Characteristics of Collaborating High Schools

 

 

 

School Zip Code % Black Fed Lunch # Sim-12’” Eligible
Students
Cody 48228 90% 65% 1051 1 16
Redford 48219 73% 30% 1521 167
Mackenzie 48204 100% 80% 1056 1 16
Mumford 48221 95% 35% 1 1 15 123
Northwestern 48208 99% 60% 824 91
Ford 48219 99% 45% 1187 130
Total/mean ******* 92% 52.5% 6754 743

 

 

45

established computer labs, minimizing disruption to other students in the classroom,
school preference and best opportunity to provide privacy.
Procedure

This study was approved by the Michigan State University Committee for Research
Involving Human Subjects (U CRII-IS) as well as the Institutional Review Board of Henry
Ford Health System.

Initial contact was made with the Ofﬁce of Research, Evaluation and Assessment
through an outside research request for the Detroit Public School System. After the
proposal was reviewed by this ofﬁce and approved, a memo that brieﬂy described the
study was developed and sent to selected school principals within the targeted area. The
Principal of each school had the opportunity to review the proposed study and to
determine whether or not they would be willing or able to participate in the project. Six
principals signed a letter of agreement to participate in the project and returned it to the
school systems research ofﬁce. Once the notiﬁcation was received by the research ofﬁce
the project manager of the Puff City program was notiﬁed, and meetings were scheduled
with Principals and designated staff to present the study purpose, and to discuss and
collaborate on implementation strategies for each school. As a result of the meetings
Principals identiﬁed one staff member from each school that would operate as the day to
day champion and contact person for the project. Principals also identiﬁed community
leaders, parent representatives and students who could assist with implementation. Plans
were developed to educate school staff such as counselors, and teachers on the
epidemiology of asthma, the related morbidity, mortality, the goals of the project, and

relevant implementation strategies.

46

Each participating school received 3 desktop computers that met speciﬁcations
according to the district protocols. The computers were installed in the designated
locations by Puff City staff. During the study the computers were to be used primarily by
students participating in the project. This was to allow participants full access to the
program while minimizing the use of existing school computers that were not accessible
at all times.

A screening survey (The Lung Health Survey [LHS], Appendix A) was developed for
the project using selected questions from validated standardized instruments including
the Youth Risk Behavior Surveillance Survey [YRBSS], the International Study of
Asthma and Allergies in Childhood [ISAAC] survey and the Fagerstrom Test for
Nicotine Dependence questionnaire. The survey included questions to determine an
established asthma diagnosis, asthma symptoms, health care utilization for symptoms,
and school days missed due to symptoms for any reason. Other items include the
student’s height, weight, smoking behavior and exposure to environmental tobacco
smoke at home.

The LHS was delivered to each school for distribution and administration by English
teachers. Passive consent was obtained from parents of all students in 9th -11th grades.
English teachers agreed that they would administer the survey during regularly scheduled
classes within a week’s time. An extension of an additional week was needed due to
factors such as teacher absences, pre-scheduled classroom activities, and teacher
discretion.

After the scannable response sheets were returned by teachers, they were forwarded to

a district vendor, Computer Management Technology (CMT) selected by the Detroit

47

Public Schools (DPS) for data processing. This step was to assure student conﬁdentiality
and anonymity prior to consent and assent to participate in the study. Using a
predetermined algorithm developed by the PI on the project, scan sheets were analyzed to
identify adolescents with a diagnosis of asthma and current symptoms (diagnosed)
undiagnosed but current asthma symptoms.

Persons in the diagnosed and undiagnosed categories were eligible for the study. As
students in the current diagnosed and undiagnosed categories were identiﬁed, a packet of
information containing a pamphlet that explained the study and the rights of research
participants, consent and assent forms, were mailed by CMS to each family. In each
packet families were given two options to return assent and consent forms. The families
could either send the forms to the schools where sealed drop boxes were located or
directly mail the forms to the PI. After students returned assent and consent forms,
demographic information and links to the LHS results were released to the PI. Students
were subsequently contacted to schedule a time for orientation to the computer, the
program and to take the baseline questionnaire.

Sample Size

There were 5,963 students in grades 9-11 of the six participating high schools that
completed the Lung Health Survey. Of the students completing the Lung Health Survey
599 students (10.1% of 5963) met the study criteria. Of the 599 students that were
eligible to participate in the study 350 (58% of 599) returned both assent and consent
forms. Therefore the number 350 will be used for purposes of power calculations.

The power and effect size tables developed by Cohen (1987) can be used to

approximate the number of subjects required to use a two tailed t-test, One-Way Analysis

48

of Variance and the Multifactorial Analysis of Variance. A two tailed t-test is used as
opposed to one tailed test when one is seeking to determine if there is a difference
between groups on an outcome such as in the current study (Munro, 2001). Power
calculations are used as a test of the null hypotheses and the likelihood of rejecting the
null hypothesis. A power of .80 is considered a reasonable value if there are few or no
previous studies to guide selecting a value (Munro, 2001). Similarly a moderate effect
size of 0.5 is also reasonable if previous research is not available as a guide of selecting
effect size. Using Cohen’s table, based on an effect size of .05 and a power of .80, the
estimated sample size needed to test for differences in the means of two groups would
be 64.

For regression analysis the formula to determine sample size is based on the effect
size index, the desired power, and the number of independent variables. The effect size
index (L) is the function of power and number of independent variables at a given level
of alpha and can be obtained from a standardized table (Cohen, 1987). According to
Cohen (1987) there are three levels of effect size. A small effect is deﬁned as an R2 of
0.02, moderate R2 of 0.13 and large as R2 of .30. For the current study a power of 0.80 at
an alpha of .05 will be used as in the previous calculations. A moderate effect size of 0.13
will be selected. The standard calculation recommended for the sample size calculations

in regression analysis is below:

49

L (l-Rz)
N= +u+l
R2

 

N = Total sample size
L + effect size index

11 = number of independent variables

 

7.78 (1- 0.13)
N = +1+1
0.13
N = 54
Measures

Gender

A self-reported gender (male or female) was included in the demographic section of
the Baseline Questionnaire.
Diagnosis

Students were classiﬁed as diagnosed using the Council of State and Territorial
Epidemiologists (CSTE) deﬁnitions for asthma prevalence as a guide (CSTE, 1995).
Physician diagnosed asthma was deﬁned as a positive response to the survey question,
“Did a doctor or other health professional ever tell you that you have asthma?” in
addition to a positive response to questions about use of prescription medication for
asthma and /or a positive response to having wheeze episodes in the last year. The latter
question was also used to distinguish students who were diagnosed, but not currently

experiencing symptoms (ever-diagnosed from those who were diagnosed and

50

symptomatic (diagnosed). Undiagnosed asthma (but symptoms consistent with asthma)
was deﬁned as reported use of medication for asthma symptoms, in addition to a report of
episodes of wheeze during the past year, in the absence of a student report of a physician
diagnosis of asthma. Students that did not ﬁrlﬁll CSTE criteria for diagnosed asthma were
classiﬁed as “no diagnosis”.
Severity

To classify participants by severity, the frequency of daytime and nighttime symptoms
used in the asthma severity classiﬁcations of the National Asthma Education and
Prevention Program Expert Panel 11 (NAEPP-II), (1997) were applied to student
responses. Investigators interpreted an assigned numeric values when terms such as
“frequent” and “continual” were used in the NAEPP-H criteria (1997).
Perceived Social Support

The Multidimensional Scale of Perceived Social Support (MSPSS) is a 12 item survey
developed by Zimet, Dahlem, Zimet, & Farley (1988) to measure perceived emotional
support (PES). The sources of support assessed in the instrument by three separate
subscales with 4 items each are friends, family and signiﬁcant other. The scale also
provides an overall global rating of perceived emotional support. The MSPSS is self-
administered, requires a fourth grade reading level and has been found to take no longer
than 10 minutes to complete. It was administered via the computer as a part of the
baseline assessment. The items from the MSPSS can be found in appendix B, number 76-
91. Responses to the MSPSS range from 1- strongly disagree to 5-strongly agree. The
instrument has been administered to demographically diverse groups of subjects across

multiple studies (Canty-Mitchell & Zimet, 2000; Cecil, Stanley, Carrion, & Swann, 1995;

51

Dahlem, Zimet, & Walker, 1991). The MSPSS has been found to be a reliable instrument
when evaluated for stability of responses over time and internal consistency. In the sited
studies the coefﬁcient alphas for the total scale ranged from .7 7-.92. Coefﬁcient alphas
for the family, friends and signiﬁcant other subscale ranged 81-93, .7 8-.94 and .79-.98
respectively. These values are indicative of strong reliability that has been established
among multiple diverse subject groups. In the current study the Chronbach’s alphas were
within the range of previous studies for the total scale and each subscale. The alpha for
the total scale was .902, and for the subscales family, .860, friends, .876 and special
person .889.
Phase of Asthma Self-Regulation Development

The Asthma Self-Regulation Development Interview (ASRDI) is a structured
interview developed by Zimmerman, et a1. (1999) to test a four phase model of self-
regulatory control of asthma (Zimmerman, et al., 1999). The ASRDI was modiﬁed to a
self-report format for the parent study in consultation with Dr. Sebastian Bonner one of
the developers of the instrument and a consultant on the parent project. The instrument
was developed to measure four sequential phases of asthma self-regulation development.
The four phases of self-regulation have been identiﬁed as (phase 1) asthma symptom
avoidance, (phase 2) asthma acceptance, (phase 3) asthma compliance, and (phase 4)
asthma self-regulation. The modiﬁed version of the instrument can be found in Appendix
B in items 47-59. Initial testing of the original instrument revealed an inverse relationship
between phase of self-regulation and asthma morbidity outcomes. In other words as
parents became more self-regulated asthma symptom days, functional limitations and

emergency department visits all declined Signiﬁcantly. In pilot testing of the instrument

52

by Zimmerman et al. (1999) the symptom experiences of children were determined by
proxy (3 parent). The current proposal will gather data directly from the affected
individual, urban adolescents. This variable will be referred to as PASRD.

Asthma Health Related Quality of Life

The Pediatric Asthma Quality of Life Questionnaire (PAQOLQ) is a self administered
measure of the disease speciﬁc ﬁmctional impairments experienced by children age 7-17.
This instrument is a 23-item questionnaire that measures the 3 domains of physical
functioning/activity limitations (5 items), emotional ﬁmctioning (8) items, and physical
symptoms (10) items.

The domains identiﬁed in the PAQOLQ are representative of the most frequently
included domains in health related quality of life. This factor allows for evaluation of
construct validity by comparison of ﬁndings among similar instruments. During
development the PAQOLQ was assessed in comparison to the Feeling Thermometer
which is a generic health related quality of life scale and the Global Rating Change
questionnaire. Children were evaluated over two study periods. The ﬁrst study period was
between weeks 2 and 5, and the second study period was between weeks 6 and 9. The
instruments were administered to the children and results were evaluated for a change in
score over time versus stability of the scores and the results were compared. A
comparison group of stable patients were identiﬁed and intraclass correlations of the ratio
of between subject variance and the total variance were determined to validate
discriminative properties. Results indicate that the PAQOLQ has high discriminative
reliability and high construct validity based on cross sectional analysis between clinic

visits (Juniper et a1. 1996).

53

When using quality of life measures it is critical to determine a value that represents a
minimal important change. This change is described as the smallest change in the
domains score that patients perceive as beneﬁcial. The score determined for the
PAQOLQ is 0.5. This score is consistent with other studies that have sought to develop
standards for change over time (Juniper et al., 1994). Determining the minimal change
will allow investigators to know at which point interventions should be stopped due to a
ceiling effect or evaluated over time for improvement when a ﬂoor effect is identiﬁed.

Youth under the age of 18 present special challenges when evaluating quality of life in
terms of ability to meaningfully complete a questionnaire. The ability to accurately
express functional limitations and changes in emotional functioning is determined by age
physical and mental health and maturity. Health providers often seek the opinions of
parents in regards to a minor child’s functional status and physical symptoms. However
parental reports in some cases do not add to the child’s report and in fact can be
inaccurate (Juniper, et al., 1997). The PAQOLQ was derived by input from children age
7-17. Developers were conscious to use the terminology of the child to minimize
difﬁculty with interpretation.

Beyond the wording of items in the instrument itself concerns also evolved around the
ability of the child to interpret the 7 point likert scale and discriminate between
responses. Testing by 37 children validated the ability of children ages 7-17 as being
reliable respondents when using the questionnaire. Intra class correlations of .95 were
determined for within subject scores. Scores were consistently high among different
domains and age groups as well. Validity of the instrument for use within children age 7-

17 was established. The only noted administrative problems with the PAQOLQ by

54

developers was the difﬁculty younger children (less than 10) experienced when
answering questions related to the concept of last week. However to overcome this
barrier, identifying an event that had occurred within the past week and rc-framing the
question within the context of the event, children were able to increase the reliability of
their responses. This variable will be referred to as QOLTot and subscales will be
referred to as QOLActivit, QOLSymptom, and QOL Emotion.

In the current study the Chronbach’s alpha was determined for each subscale and for
the total scale. Previous studies using the PAQOLQ have not reported this value (Guyatt,
Juniper, Grifﬁth, Feeny, & Ferric, 1997; Juniper, Guyatt, Feeny, Grifﬁth, & Ferric, 1997;
Juniper, Guyatt, Feeny, Ferric, Grifﬁth, & Townsend, 1996. A limitation of the current
estimated values is that one item from the physical symptom subscale is missing and
students completing the items on the activity subscale entered more than one value for
items listed. An average of the values entered was accepted as the ﬁnal score. The total
scale alpha was .903. The apha’s for the subscales were as follows; Activity Limitations,
.707, Physical Symptoms, .921 and Emotional Functioning .920. Each alpha except the
Activity limitations subscale was above the desirable subscale of .80 (Munro, 2001).
Further testing will be needed to determine if the scoring procedure of the current study
contributed to the lower alpha as opposed to the reliability of the subscale.

Asthma Health Outcomes

Hospitalizations and Emergency department visits were quantiﬁed using items similar
to those used in the National Cooperative Inner City Asthma Study and the Behavioral
Risk Factor Surveillance Survey which examined asthma morbidity over periods of 2

weeks and 12 months respectively (Centers For Disease Control & Prevention, 2000

55

[CDC]; Mitchell etal., 1997). This strategy allows us to compare ﬁndings in the current
proposal to those found in national sammcs.

Subjective asthma symptoms are important health outcome indicators. Youth affected
by asthma report symptoms of asthma such as wheezing, cough, difﬁculty breathing,
disturbances in sleep, ﬁmctional limitations in age appropriate activities such as Sports,
missed work, missed school and embarrassing intrapersonal social experiences related to
asthma (Yeatts & Shy, 2001). Additionally when compared to healthy peers, youth with
asthma report lower perceived well-being, and greater emotional symptoms (Creer, Stein,
Rappaport, & Lewis, 1992; Taylor, & Newachcck, 1992; Nacon, & Booth, 1991)

Asthma symptoms were quantiﬁed based on self-report of experiences for the past 30
days. Youth were asked if they experienced asthma symptoms, restricted their activity
due to symptoms or were awakened at night due to symptoms. These outcomes include
those recommended by the NHLBI Expert Panel 11 report (1997) for the assessment of
asthma severity and morbidity. Further asthma symptoms such as cough and wheeze have
been identiﬁed by youth as a signiﬁcant source of embarrassment that interfere with

feelings of normalcy.

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60

Data Analysis

The demographic characteristics of the study participants, and each major variable
were analyzed using descriptive statistics. The analysis included frequencies, measures of
central tendency, measures of variability, and cross tabulations. To test the differences
between group means t-test and one-way analysis of variance (AN OVA) was used.
Descriptive statistics were calculated for age, gender, race, grade, and diagnosis of
asthma for the total population. Additionally each variable was analyzed to determine if
there were signiﬁcant differences between the means based on gender, diagnosis, and
asthma severity. When analyzing subscales for differences between scales, t—test, were
used to determine if there were signiﬁcant differences between the scales. All instruments
were tested for reliability using Chronbach’s alpha.
Research Questions & Planned Analysis

Each research question and the planned analysis are presented below:
Question 1: What is the perception of emotional support among urban adolescents with
asthma?
Analysis: Descriptive statistics including means, and standard deviations were used for
analysis of each subscale and the total scale. Paired t-test for independent samples was
also used to determine if the mean differences between the various sources of support
were signiﬁcantly different.
Question 2: Does PES differ by gender, diagnosis, or asthma severity?
Analysis: To determine if there were signiﬁcant mean differences by gender, diagnosis
or asthma severity a separate One-Way ANOVA was run using gender, diagnosis and

asthma severity as the factors.

61

Question 3: Does Phase of Asthma Self Regulation Development (PASRD) differ by
gender, diagnosis, or severity?

Analysis: The Crosstabulation procedure was employed to determine the number of
persons in each phase of asthma self-regulation development by gender, diagnosis and
severity. Next the Chi Square statistic was computed separately for each group (gender,
diagnosis and severity) to determine if the differences in the frequencies were statistically
signiﬁcant.

Question 4: What is the relationship between PBS and PASRD?

Analysis: Initially a MANOVA was run to examine the mean differences in PBS by
PASRD. Secondly to test for an association linear regression was employed.

Question 5: What is the relationship between PBS and Disease Self-Management
Behavior?

Analysis: Linear regression was employed to determine if there was a relationship
between PBS and Disease Self-Management.

Question 6: What is the relationship between PASRD and Disease Self-Management
Behavior?

Analysis: Linear regression was employed to determine if there was a relationship
between PASRD and Disease Self-Management.

Question 7: What is the effect of PASRD on the relationship between PES and Disease
Self-Management Behavior?

Analysis: Disease Self-Management Behavior was hypothesized as a mediator or a
moderator in the relationship between PBS and Asthma Health Related Quality of Life. In

order to determine if this hypothesis held, several steps were employed. First linear

62

regression was employed to determine the relationship between PBS and the dependent
variable Asthma Health Related Quality of life. Second linear regression was used to
determine the association between PBS and the mediator Disease Self-Management.
Finally multiple regression was used entering PBS and Disease Self-Management
Behavior simultaneously with Asthma Health Related Quality of Life as the outcome.
Secondly a moderation model was tested using multiple regression. In this analysis the
terms PBS and PASRD were entered ﬁrst followed by the interaction term PES*PASRD
with Asthma Health Related Quality of Life as the outcome.

Question 8: What is the effect of Disease Self—Management Behavior on the relationship
between PBS and Health Outcomes?

Analysis: Disease Self-Management Behavior was hypothesized as a mediator or a
moderator in the relationship between PASRD and Health Outcomes. The steps outlined
in question 7 were used to test both mediation and moderator models using the
appropriate variables for the current question.

Question 9: What is the effect of Disease Self-Management Behavior on the relationship
between PBS and Asthma Health Related Quality of Life?

Analysis: Disease Self-Management Behavior was hypothesized as a mediator or a
moderator in the relationship between PBS and Asthma Health Related Quality of Life.
The steps outlined in question 7 were used to test both mediation and moderator models
using the appropriate variables for the current question.

Question 10: What is the effect of Disease Self-Management Behavior on the

relationship between PASRD and Health Outcomes?

63

Analysis: Disease Self-Management was hypothesized as a mediator or a moderator in
the relationship between PASRD and Health Outcomes. The steps outlined in question 7
were used to test both mediation and moderator models using the appropriate variables
for the current question.

Question 1 1: What is the effect of Disease Self-Management Behavior on the
relationship between PASRD and Asthma Health Related Quality of Life?

Analysis: Disease Self-Management was hypothesized as a mediator or a moderator in
the relationship between PASRD and Asthma Health Related Quality of Life. The steps
outlined in question 7 were used to test both mediation and moderator models using the
appropriate variables for the current question. As a result of ﬁndings that suggested a
negative relationship between PASRD and Asthma Health Related Quality of Life
Hierarchical Regression was employed to determine the contribution of gender,

diagnosis, and asthma severity towards explaining this relationship.

64

Chapter 4
RESULTS

Descriptive statistics for the demographic characteristics of the study population will
be presented ﬁrst followed by descriptive statistics for the study variables stratiﬁed by
gender, diagnosis, and severity of asthma. Questions 1-3 will be answered in this section
of the chapter as these questions pertain to descriptive ﬁndings within the study
population. Finally each research question will be stated followed by the analysis used to
answer the question.

In the current study as previously identiﬁed, youth with a diagnosis of asthma and
current symptoms and youth with current symptoms and no diagnosis were eligible to
participate. The inclusion of youth without an asthma diagnosis may have in part
contributed to skip patterns in the responses as some questions were not clearly
applicable to each participant. Although some participants opted not to respond to all
questions the results presented includes all available data. The inclusion of all available
data resulted in changes in the denominator for the different scales and subscales within
the following results section. All statistical analysis for the study was completed using
the Statistical Package for Social Sciences (SPSS) version 11.5 for windows.

Sample Characteristics

Participants in the study ranged in age ﬁom 13-18 with a mean age of 15.29. There
were more female participants than males, 194 (63.3%) verses 111 (36.4%) respectively.
The majority of students were in grade 9 (118, 38.7%) followed by grade 10 (105,
34.4%) and 11 (73, 23.9%), while the fewest were in grade 12 (4, 1.3%). Although

students in grade 12 were not recruited or eligible to participate in the study ﬁve

65

inadvertently took the baseline survey which is the source of the data for the research
presented. The exclusion of 12th grade students was more important for the parent study
due to the need for completion of a one year intervention and one year follow up.
Because there was no rationale to delete the students from the supplemental study the
data was included in all analysis. Participants were asked if they were enrolled in a
Medicaid insurance plan. Of the 294 persons responding to this question, 141 (46.2%)
answered yes, 43 (14.1%) answered no, and 110 (36.1%) answered don’t know (see
Table 3).

Covariates: Gender. Each study variable was compared by gender to determine if males
and females differed signiﬁcantly. All of the results with the exception

of those that apply to the PES variable and PASRD are discussed in the following
section. The results for the PES variable are discussed in the section that addresses
research question number one and the PASRD results will be discussed in the section that
focuses on research question number 3. Analysis for gender differences helped to
determine if adolescents with asthma varied signiﬁcantly indicating a need for gender
speciﬁc interventions.

DSM and each health outcome variable were analyzed using one-way AN OVA to test for
differences between means by gender. No statistically signiﬁcant differences were found
(see Table 4). Signiﬁcant gender differences were found for the asthma health related
quality of life variable. The total scale results were F (1, 250) = 1.064, MSE = 19.18, p =
.002. The mean score for males was signiﬁcantly higher than females, 5.57, SD = 1.25
and M = 4.98, SD = 1.48 respectively. These results indicated that males reported greater

asthma health related quality of life than females.

66

Table 3

Demographic Characteristics of Study Population (N = 305)

 

 

Variable n % M SD Range
Age 303 15.26 1.00 13-18
Gender

Male 1 1 1 36.4

Female 194 63.6

Race

Black 272 89.2

Other 28 10.8

Grade

9th 1 18 38.7

10th 105 34.4

1 1th 73 23.9

12th 4 1 3

Insurance

Medicaid 141 46.2

 

67

Diagnosis of Asthma.

There were 199 (65.2%) participants that reported a diagnosis of asthma and current
symptoms of asthma and 98 (32.1%) that did not have a diagnosis of asthma but who
reported respiratory symptoms consistent with asthma. Of those with a diagnosis of
asthma 64.8% were females. Of those without a diagnosis 61.2% were females. There
were no signiﬁcant differences by diagnosis between males and females x2 = .368, p =
.608.

Analysis of the remainder of the study variables by diagnosis revealed several
statistically signiﬁcant differences. Each study variable mean was greater for persons
with a diagnosis of asthma however, only 3 variables reached statistical signiﬁcance.
Using a one-way AN OVA, DSM, number of ER visits, and QOLTot each demonstrated
statistically signiﬁcant mean differences (see Table 5). The mean number of
hospitalizations for the study population trended toward signiﬁcance, p = .063. The mean
value of DSM for persons without a diagnosis was .27, (SD = 2.28) compared to persons
with a diagnosis (M = 3.98, SD = 3.01). These results indicated that persons with a
diagnosis of asthma carried their inhaler more often than persons without a diagnosis.
There were fewer emergency department visits for persons without a diagnosis (M = .27,
SD = .657) compared to persons with a diagnosis (M = 1.21, SD = 3.01). This may
indicate less disease severity among persons not diagnosed. Disease severity by diagnosis
will be discussed later. On the quality of life total scale, the mean was lower for persons
with a diagnosis (M = 4.97, SD =1.43) compared to persons without a diagnosis (M =
5.63, SD = 1.36). This ﬁnding indicated poorer quality of life among person’s with a

diagnosis of asthma. See Table 5 for the remaining means of study variables.

68

Asthma Severity.

Over half of the participants, (175, and 57.4%) were found to meet criteria for the
mild intermittent asthma severity classiﬁcation. The remainder of the participants asthma
severity classiﬁcations were as follows, mild persistent 45(14.8%), moderate persistent
59 (19.3%), and severe persistent 23, (7.5%).

Asthma severity was ﬁrst stratiﬁed by asthma diagnosis. Among persons with a
diagnosis of asthma 99 (49.7%) were classiﬁed within the mild intermittent category
compared to 71 (73.2) persons without a diagnosis. See Table 6 for the remaining
classiﬁcations by diagnosis. The relationship between these variables was further
analyzed to determine if there were signiﬁcant differences between participants by
diagnosis and severity classiﬁcation. The Chi Square test indicated that there were
signiﬁcant differences between the two groups (x2 = 16.13, p = .001) (see Table 6).

Next asthma severity was stratiﬁed by gender to determine the count and the
percent of males and females within each classiﬁcation. Among males 64 (58.7%) met
criteria for the mild intermittent asthma as compared to 111 (57.5%) females within this
classiﬁcation. Few participants met criteria for severe persistent asthma. Of the
participating females 17 (8.8%) were classiﬁed as severe persistent and for males 6
(5.5%) were within this category. Refer to Table 7 for the additional frequencies for the
remaining categories of asthma severity by gender. To further analyze the relationship
between these two variables, the Chi Square test for signiﬁcance was conducted for
severity classiﬁcation to determine if males and females differed. The results were not
signiﬁcant, (x2 = 5.141, p = .162) indicating that males and females did not differ by

disease severity.

69

Table 4

One-Way ANOVA of Study Variables by Gender

 

 

Variable df MSE F p - value
1
DSM 181 10.22 1.06 .304
1
Numervis 297 9.60 3.44 .065
1
Numhosp 229 1.21 .380 .538
Activity 1
Affected 300 74.55 1.31 .253
1
Symptom Days 302 32.18 .657 .418
1
Nights 300 38.80 1.17 .280
Awakened
1
QOLTot 250 19.81 9.94 .002

 

70

Table 5

Means, SD and One-Way ANOVA of Study Variables by Diagnosis

 

 

Variable n M SD df MSE F p — value
DSM
No .23 .96 2.28 1
Yes 158 3.98 3.01 179 183.65 21.34 .000
Numervis
No 96 .27 .657 1
Yes 197 1.21 3.01 291 56.70 9.07 .003
Numhosp
No 56 .18 .636 1
Yes 170 .69 2.03 224 11.19 3.49 .063
Symptom
Days
No 97 5.1 1 7.38 1
Yes 199 5.83 6.90 294 33.40 .670 .414
Activities
Affected
No 97 4.40 7.46 1
Yes 199 5.92 7.60 294 151.17 2.64 .105
Nights
Awakened
No 97 2.49 5.49 1
Yes 199 3.48 5.93 294 63.60 1.89 .170
QOLTot
No 82 5.63 1.36 1
Yes 153 4.97 1.43 243 23.29 11.65 .000
QOLSymp
No 86 5.59 1.45 1
Yes 171 4.91 1.55 255 26.16 11.31 .001
QOLActiv
No 93 4.97 1.55 1
Yes 189 4.35 1.51 280 24.01 10.29 .001
QOLEmot
No 90 6.14 1.34 1
Yes 1.87 5.35 1.60 275 37.62 16.16 .000

 

71

Next study variables were analyzed to detect differences between the means at each
level of asthma severity. The variables Symptom Days, Activity Affected and Nights
Awakened were not included in this analysis as they also represented aspects of asthma
severity. The means for each study variable when stratiﬁed by asthma severity were
statistically signiﬁcant (see Table 8). The mean value for each of the variables was
lowest at the mild intermittent level of severity and all study variables increased in value
for each level of asthma severity with the exception of DSM and QOL. The means for the
DSM variable were less predictable in that the means were lowest for the mild
intermittent level (M = 2.79, SD =3.15) followed by the severe persistent level (M = 3.21,
SD =2.80). The mild persistent level (M = 3.96, SD = 2.83) and the moderate persistent
level (M = 5.02, SD =2.72) were the highest means. The ﬁnding that means were lower
for adolescents with severe persistent asthma may represent a blurring of severity as
perceived by the affected individual when symptoms reach a severe persistent level. See
Table 9 for a listing of all of the mean scores by variable and asthma severity.

The quality of life variable was highest at the mild intermittent level (M = 5.77, SD =
.651) and the value declined with increasing asthma severity indicating worsening quality
of life with increasing asthma severity (see Table 9).

Predictor Variables: Perceived Emotional Support

Perceived Emotional Support was analyzed to determine the mean scores of the total
scale and subscales (Family, Friends, Special Person). Descriptive and inferential
statistical techniques were used to analyze PES. This analysis provided the analytical

response to research questions number one and two.

72

Table 6

Crosstabulation of Asthma Severity by Diagnosis

 

 

 

Severity
Mild Mild Moderate Severe Total
Intermittent Persistent Persistent Persistent
Nodiagnosis 71 11 9 6 97
% Within Nodiagnosis 73.2 % 11.3 % 9.3 % 6.2% 100%
Diagnosed 99 33 50 17 199
% Within Diagnosed 49.7 % 16.6 % 25.1 % 8.5 % 100 %

 

Chi Square = 6.13, p = .001

73

Table 7

Crosstabulation of Asthma Severity by Gender

 

 

 

Severity
Mild Mild Moderate Severe Total
Intermittent Persistent Persistent Persistent
Male Count 64 12 27 6 109
% Within GENDER 58.7 % 11.0 % 24.8 % 5.5% 100 %
Female Count 111 33 32 17 193
% Within GENDER 57.5 % 17.1% 16.6 % 8.8 % 100 %

 

Chi Square = 5.141, p =.

'1 62

74

I. What is the perception of emotional support among urban adolescents with
asthma?
2. Does PES differ by gender, diagnosis, or asthma severity?

The overall mean for the PES scale was 4.01, (SD = 0.73). The mean score for the
special person subscale was highest at 4.12 (SD = .90), followed by the ﬁiends subscale
(M =3.98, SD = 0.89 and the family subscale (M =3.93, SD =.91) (see Table 10). The
possible range of scores was 1-5 with higher scores indicative of greater PES. Paired
sample t-test of the subscales was employed to determine if the differences between the
means were signiﬁcant. Results indicated that family and special person (t = 3.70,
p<.000) and ﬁiend and special person (t = -2.72, p =.007) were signiﬁcantly different
(see Table 11).

Next multivariate analysis of variance was employed to determine the main effects
and interactions for gender, diagnosis, and asthma severity on PES. Gender was the only
variable that demonstrated a main effect on PBS (F = 7.32, df 3, p = .000).

See table 12 for the complete analysis. There were no signiﬁcant interactions between the
variables Gender * Severity, or Gender*diagnosis on PES. In order to further understand
the main effect of gender on PES, subscale tests for between subject effects were
reviewed. All subscales except family were found to be signiﬁcant by gender, ﬁiend

(F =11.01, (if 1, p = .001), and special person (F =10.35, df 1, p = .001) (see Table 13).
The means for males (3.89) and females (3.90) on PESFamily subscale failed to reach
statistical signiﬁcance. However, the remaining means for the subscales for PESTot,

PESFriends, & PESSpecial were all greater for females than males (see Table14). These

75

Table 8

One-Way Analysis of Variance of Study Variables by Asthma Severity

 

 

Variable df F p - value
DSM 3 6.04 .001
1 79
Numervis 3
292 10.85 .000
3
Numhospi 226 5.87 .001
3
QOLTot 245 26.6 .000

 

76

Table 9

Means and SD of Study Variables by Asthma Severity

 

 

Variable n M SD
DSM
Mild Intermittent 97 2.79 3.15
Mild Persistent 27 3.96 2.83
Moderate Persistent 46 5.02 2.72
Severe Persistent 14 3.21 2.80
Numervis
Mild Intermittent 171 .36 .859
Mild Persistent 44 .70 1.35
Moderate Persistent 58 1.81 3.96
Severe Persistent 23 2.87 5.17
Numhosp
Mild Intermittent 122 .21 .718
Mild Persistent 37 .49 1.04
Moderate Persistent 53 1.08 2.80
Severe Persistent 18 1.72 3.19
QOLTot
Mild Intermittent 143 5.77 1.15
Mild Persistent 39 4.51 1.21
Moderate Persistent 48 4.48 1.53
Severe Persistent 19 3.80 1.36

 

77

ﬁndings indicate that overall females perceive greater emotional support, than males and
that this ﬁnding holds true when sources of support are from friends and special persons .
Phase of Asthma Self-Regulation Development

Phase of Asthma Self-Regulation Development (PASRD) was analyzed to describe
the number and percent of persons that met criteria for each of the 4 phases. Most
participants met criteria for phase 1(138, 45.2%). The fewest number of participants met
criteria for phase 2 (28, 9.2%). The remaining participants were distributed as follows,
phase 3 (78, 25.6%), and phase 4 (59, 19.3%). Phase of Asthma Self-Regulation
Development was also analyzed to determine if there was variation by gender diagnosis,
and severity. This analysis'answered research question number three.

3. Does Phase of Asthma Self-Regulation Development diﬂer by gender, diagnosis, or
asthma severity?

Cross tabulations were employed to determine the frequencies at each phase of self-
regulation development. Further the Chi Square statistic was used to identify if the
differences between the groups were statistically signiﬁcant. When PASRD was stratiﬁed
by gender, more females were represented at each level. Signiﬁcant differences between
males and females were found at phase I (x2 = 4.03, p = .045) and phase II (12 = 4.39,
p= .036), but not at phase III or phase IV (see Table 15). Of the 295 persons responding
to the PASRD questions, 96 did not have a diagnosis of asthma. There was a statistically
signiﬁcant difference between persons with a diagnosis of asthma and persons without a
diagnosis at phase I ( x2 = 49.12, p < .000), phase 111 (x2 = 19.98, p < .000) and phase

IV (x2 = 16.81, p < .000) (see Table 16).

78

Table 10

Means and SD of Overall PBS and Subscales

 

 

PES Scale n Mean SD

PESTotal 297 4.01 0.73
PESFamily 298 3.93 0.91
PESFriends 302 3.98 0.89
PESSpecial 303 4.12 0.90

 

79

Table 11

Pairwise Comparisons of Sources of PES

 

 

PES Sub-Scales t-Value p-values
PESFamily * PESFriend .831 .407
PESFamily * PESSpecial 3.70 < .000
PESFriend * PESSpecial -2.72 .007

 

80

Table 12

Multivariate Analysis of PES by Gender, Asthma Severity, and Diagnosis

 

 

Variable F df Sig.
Gender 7.32 3 p < .000
Severity .245 9 p = .988
Diagnosed 1.45 3 p = .226
Gender*Severity 1.12 9 p = .280
Gender*Diagnosis .548 3 p = .650
Severity*Diagnosis 1.34 9 p = .208

 

81

Table 13

Test of Between Subject Effects for PBS by Gender

 

 

Variable F df p value
PESTotal 7.02 l p = .009
PESFamily .004 1 p = .951
PESFriend 11.01 1 p = .001
PESSpecial 10.35 1 p = .001

 

82

Table 14

Estimated Marginal Means for PBS by Gender

 

 

 

Dependent Gender Mean Std. Error 95% Conﬁdence Interval
Variable
Lower Bound Upper Bound
PESTotal Male 3.79 .126 3.54 4.04
Female 4.16 .075 4.01 4.31
PESFamily Male 3.89 .160 3.58 4.21
Female 3.90 .095 3.72 4.09
PESFriend Male 3.69 .150 3 .40 3 .99
Female 4.25 .089 4.08 4.43
PESSpecial Male 3.77 .154 3 .47 4.08
Female 4.332 .091 4.15 4.51

 

83

Next PASRD was analyzed using the crosstabulation procedure to determine the
differences between participants at each phase of asthma self-regulation development by
asthma severity. The highest percentage of participants at phase I, were categorized as
Mild Intermittent (97, 56.1%). At phase II, the greater percentage of participants was
categorized as Severe Persistent (4, 17.4%). Phase III and Phase IV were similar in that
the greatest percent of participants met criteria for the Moderate Persistent category of
asthma severity (19, 32.2%) and (19, 32.2%) respectively. See Table 17 for the additional
crosstabulation results.

Disease Self-Management Behavior

Persons with asthma are directed to always keep their rescue inhaler close enough for
quick use. In this study participants that had an inhaler kept it near slightly more than
half of the time within the past 7 day period (M =3.56, SD = 3.10). Analysis for
differences between males and females on Disease Self-Management Behavior was not
signiﬁcant (F (1, 181) = 1.06, MSE = 10.22, p = .304. Further analysis demonstrated that
participants with a diagnosis of asthma carried an inhaler more often than participants
without a diagnosis. Although this ﬁnding was statistically signiﬁcant (F =7.04, df 1,

p = .009 it should be interpreted cautiously. Of the students responding to this question
62 (20.3%) reported carrying an inhaler zero days. This response may be indicative of
behavior or it may represent persons that did not have an inhaler. Statistically signiﬁcant
differences also were found by severity for participants in terms of carrying their inhaler
(F (3, 179) = 6.04, MSE = 53.6, p = .001. In general the means of DSM increased as

severity increased. The exception to the trend of this analysis was for the severe

84

persistent category where the mean was found to be the second highest of all categories.
See Table 9.
Health Outcomes

Health outcomes consisted of emergency department visits, hospitalizations and the
following 3 items that represented asthma symptom experiences over the past 30 days;
(1) number of days that asthma symptoms were experienced, (2) number of days
activities were changed due to asthma symptoms and (3) number of nights awakened by
asthma symptoms. Participants reported a mean of 0.89, (SD, 2.51) emergency
department visits and a mean of 0.57 (SD, 1.79) hospitalizations over the past 12 months.
Asthma symptoms experiences over the past months were as follows; symptom days
M = 5.37, SD = 7.53, days activities changed M = 5.52, SD = 6.99, and nights awakened
M = 3.1, SD = 5.75.

Each health outcome was analyzed by One-way AN OVA for differences by gender,
diagnosis, and asthma severity and has been discussed in previous sections.
Asthma Health Related Quality of Life

Asthma Health Related Quality of Life was analyzed for total scale scores followed by
subscale scores. The possible range for the mean scores is 0-7 for the total AHRQOL and
the subscales, with higher scores indicative of better quality of life. The means of each
subscale were compared for signiﬁcant differences using pairwise comparisons.

The mean for the total scale score was 5.198, SD, 1.434. The mean score for the
emotional functioning subscale was highest at 5.618 (SD =1.55), followed by the
symptoms subscale (M = 5.138, SD =1.552) and the activity limitations subscale (M =

4.56, SD = 1.53). Next each subscale was paired and compared for statistically signiﬁcant

85

differences between subscales. Pairwise comparisons using t-test indicated that the means
of each subscale were signiﬁcantly different from the other (see Table 18).

QOL was analyzed using One—way ANOVA’s to examine this variable for mean
differences by gender, diagnosis and severity. The results for this analysis have been
discussed previously.

Research Questions

In the following section of this chapter the results of the study will be presented
according to the remaining research questions posed beginning with question number 4.
Question 4: What is the relationship between PES and PASRD?

PES total scale scores and each individual subscale score was utilized in this analysis.
The subscale analysis were conducted due to the variation in source of support
represented by each subscale (family, ﬁiend and special person) to determine if the
source of support affects PASRD differently. The Phase of asthma self-regulation
differed also in terms of identifying the point at which the individual was currently self-
regulating their asthma. Therefore each phase of asthma self-regulation development was
also be analyzed to determine if PES varies at each phase.

To evaluate the differences in the mean score for each source of support at the four
phases of asthma self-regulation development a MAN OVA was conducted. The results
revealed statistically signiﬁcant differences in the means for SocTotal and for each
subscale by phase of self-regulation development, SocTotal (F, (3) = 5.24, p = .002),
SocFamily (F (3) = 5.49, p = .001), SocFriend, (F (3) = 3.03, p = .029, and SocSpec (F
(3) = 3.74, p = .012) see Table 19. The mean PES score for total support and each

subscale were consistently highest at phase IV of asthma self—regulation development

86

Table 15

Crosstabulation of PASRD by Gender

 

 

PASRD Gender 11 (%) Chi Square p-value

Phase I Male 58 (53.2) 4.034 .045
Female 80 (41.2)

Phase 11 Male 5 (4.6) 4.39 .036
Female 23 (11.9)

Phase 111 Male 25 (22.9) .702 .402
Female 53 (27.3)

Phase IV Male 21 (19.3) .005 .946
Female 38 (19.6)

 

% = percent within Gender

87

Table 16

Crosstabulation of PASRD by Diagnosis

 

 

PASRD n (%) Chi Square p-value
Diagnosis

Phase I No 71 (74) 49.12 .000
Yes 61 (30.7)

Phase II No 10 (10.4) .142 .707
Yes 18 (9.0)

Phase 111 No 9 (9.4) 19.98 .000
Yes 67 (33.7)

Phase IV No 6 (6.3) 16.81 .000
Yes 53 (26.6)

 

% = percent within diagnosis

88

Table 17

Crosstabulation of PASRD by Asthma Severity

 

 

PASRD Mild Mild Moderate Severe
Intermittent Persistent Persistent Persistent

n (%) n (%) n (%) n (%)
Phase I 97 (56.1) 18 (40.0) 13 (22.0) 7 (30.4)
Phase II 9 (5.2) 7 (15.6) 8 (13.6) 4 (17.4)
Phase III 44 (25.4) 10 (22.2) 19 (32.2) 5 (21.7)
Phase IV 23 (13.3) 10 (22.2) 19 (32.2) 7 (30.4)

 

% = percent within severity

89

(M = 4.33, SD = .553), family (M = 4.28, SD = .675), ﬁiends (M = 4.26, SD = .801), and
special person (M = 4.44, SD = .673) see Table 19. The mean PES scores were also
consistently lowest at phase II of asthma self-regulation development with the exception
of PBS Friends.

Regression analysis was conducted next to determine if PBS was associated with
PASRD. Total PES was a signiﬁcantly associated with PASRD (R = .150, B = .247,
MSE .095, B = .150, p = .010. However, despite the statistical signiﬁcance, PES failed to
explain a reasonable amount of the variance in PASRD, R2 = .02. Due to this ﬁnding,
ﬁrrther analysis by subscales was not performed.

Question 5: What is the relationship between PES and Disease Self-Management
Behavior?

To test the relationship between PES and disease self-management regression
analysis was conducted. Total PES was not found to be a signiﬁcant predictor of DSM (R
= .121, B = .522, MSE, .322, B = .121, t = 1.62, p = .107.

Question 6: What is the relationship between PASRD and Disease Self Management
Behavior.

This relationship was also tested by regression analysis. PASRD was found to be a
signiﬁcant predictor of DSM (R = .285, B = .747, MSE = .187, B = .285, t = 1.62,

p < .000. PASRD was found to explain 8 percent of the variance of DSM, R2 = .081. In
general, mean DSM behavior increased sequentially with each phase of asthma self-
regulation development (M = 2.51, SD = 3.00, M = 3.54, SD = 2.72, M = 3.31, Sad =
3.11, M =5.04, SD = 2.77). The exception in this ﬁnding was that the mean of phase 2

was greater than the mean of phase 3. The results indicate that as phase of asthma self-

90

Table 18

Pairwise Comparison of QOL Subscales

 

 

Variable t p — value
QOLSymp*QOLActiv -8.36 .000
QOLSymp*QOLEmot -8.56 .000
QOLAct*QOLEmot -14.06 .000

 

91

regulation development increased the participant was more likely to carry their rescue
inhaler.
Question 7: What is the effect of PASRD on the relationship between PES and DSM?
Phase of asthma self-regulation development could potentially have either acted as a
mediator or moderator on the relationship between PBS and DSM. Mediators identify
how an association occurs between an independent variable and a dependent variable
(Bennett, 2000). Prior to testing for a mediator effect, there must ﬁrst be a statistically
signiﬁcant relationship between an independent variable and a dependent variable
(Bennett, 2000). In the current study as tested previously by regression analysis, there is
not a signiﬁcant relationship between PES and DSM. Therefore the potential for a
mediation effect could not be tested.

Moderators differ from mediators in that they affect the strength and or direction of
associations between an independent variable and a dependent variable (Bennett, 2000).
When testing for a moderator affect of a variable, a signiﬁcant relationship does not have
to exist between the independent variable and dependent variable the moderator is
expected to affect.

To answer question 7, a test for an interaction between PBS and PASRD using
regression analysis was performed. Regression analysis testing for the moderating role of
PASRD indicated that the interaction term (PES * PASRD) accounted for a signiﬁcant
portion of the variance of disease self-management beyond that accounted for by PES
and PASRD alone, chhange = .100, F change (3, 175) = 6.49, p < .000 (see Table 20 for
regression analysis). These results indicate that PASRD moderates the relationship

between PES and DSM.

92

Table 19

Multivariate Analysis of PBS by PASRD

 

 

PES n M SD F df p - value
PASRD

PESTotal 5.24 3 .002
1 134 3.95 .652

2 28 3.80 1.01

3 74 3.93 .822

4 59 4.33 .553

PESFamily 5.49 3 .001
1 134 3.91 .900

2 28 3.48 1.24

3 75 3.88 .884

4 59 4.28 .675

PESFriend 3.03 3 .029
1 137 3.95 .81 1

2 28 3.93 .999

3 76 3.81 1.01

4 59 4.26 .801

PESSpecial 3.74 3 .012
1 137 4.00 .879

2 28 3.98 1.17

3 77 4.12 .937

4 59 4.44 .673

 

93

Question #8: What is the effect of Disease Self-Management Behavior on the relationship
between PES and Health Outcomes?

In testing the effect of DSM on the relationship between PES and health outcomes
the same strategy was used as in question seven. A mediation effect was hypothesized in
the study model. However due to the fact that the PBS was not a signiﬁcant predictor of
any of the health outcomes there was no relationship to mediate (see Table 21).

Next a moderation effect is tested. In step one of the regression analysis PES and
PASRD were entered as predictors of the health outcome variables. The ﬁrst step allows
the researcher to see the main effects of each independent variable on the dependent
variable. The results of this analysis do not have to demonstrate a signiﬁcant relationship
between the independent variables and the outcome variables (Bennett, 2000). During
step two, the interaction term that represented the joint relationship between PBS and
PASRD was entered to test for a moderation effect. In this step of the analysis the
interaction term must explain a statistically signiﬁcant amount of the variance in the
dependent variable to demonstrate a moderator effect (Bennett, 2000). In this study there
were no signiﬁcant effects between the interaction term PES*PASRD and any of the
health outcomes (see Table 22).

Question #9: What is the effect of Disease Self-Management Behavior on the relationship
between PES and Asthma Health Related Quality of Life?

The ﬁrst step to test for a mediation effect was to regress PES on the dependent

variable QOL. Results indicated that there was no signiﬁcant relationship between PES

94

Table 20

Regression Analysis for the Moderator Effect of PASRD on the Relationship between
PES and DSM

 

 

IV DV R B SE [3 t p - value
PESTot DSM .317 -1.08 .792 -.251 -1.36 .173
PASRD -1.46 1.21 -.562 -1.20 .229
PESTot*PASRD .527 .291 .965 1.81 .072

 

95

Table 21

Regression Analysis of PES on Health Outcomes

 

1v DV R R2 B SE B t p-value

 

PESTot Numervis .001 .000 .004 .203 .001 .021 .983

NumHosp .121 .015 -.294 .162 -.121 -1.81 .071
Symptom .034 .001 .311 .539 .034 .577 .564
Days

Activity .011 .000 -.109 .585 -.011 -.186 .853
Affected

Nights .056 .003 .408 .428 .056 .953 .341
Awakened

 

96

and QOL, (R = .071. B = .143, SE = .128, [3 = .071, t = 1.11, p = .267). Therefore criteria
for a mediation effect could not be pursued. Test for a moderating effect of DSM on the
relationship between PBS and QOL were conducted next. In this analysis the variables
were entered into the regression model as indicated previously to test for a moderator
effect. Results indicated no statistically signiﬁcant effect of the interaction between the
variables PES and DSM on QOL (see Table 23).

Question #10: What is the eﬂect of Disease Self-Management Behavior on the
relationship between PASRD and Health Outcomes?

Again the initial analysis included test for the main effect of PASRD on the dependent
variables for the health outcomes was performed. Results of this analysis demonstrated
several statistically signiﬁcant relationships. PASRD had a signiﬁcant main effect on
number of emergency department visits R2 = .152, SE = .120, t = 2.64, p = .009. There
was also a statistically signiﬁcant effect of PASRD on days activities affected (p = .017),
and nights awakened (p = .027) (see Table 24). The main effect for PASRD on symptom
days trended towards signiﬁcance, p = .076. Next analysis was run to test for a main
effect of PASRD on the mediator DSM. This analysis was completed for question 6 and
demonstrated a signiﬁcant relationship.

The ﬁnal step in a mediator analysis is to enter the independent variable, mediator
variable, and outcome variables simultaneously. To detect a mediator effect, the mediator
must be a signiﬁcant predictor of the outcome variable and the direct relationship of the
independent variable to the outcome variable is less signiﬁcant than it was in the second
equation (Baron & Kenny, 1986). Each outcome variable that reached statistical

signiﬁcance was entered in a separate equation. Results did not identify any mediation

97

Table 22

Regression Analysis for the Moderation Effect of DSM on the Relationship between PES
and Health Outcomes

 

 

IV DV R B SE [3 t p-value
PESTotal Numervis .1 1 1 .231 .518 .053 .446 .656
DSM .422 .463 .41 1 .912 .363
PESTotal*DSM -.079 .112 -.331 -.704 .482
PESTotal Numhosp .173 -.381 .414 -.126 -.921 .359
DSM .115 .346 .166 .333 .740
PESTotal*DSM -.009 .084 -.057 -.11 l .912
PESTotal Activity .241 .591 1.13 .059 .521 .603

Affected
DSM 1.94 1.02 .837 1.90 .058
PESTotal*DSM -.355 .247 -.658 -1.43 .152
PESTotal Symptom .238 .609 .973 .071 .626 .532
Days
DSM 1.38 .874 .697 1.58 .114
PESTotal*DSM -.230 .212 -.498 -1.08 .278
PESTotal Nights .127 .215 .830 .030 .259 .796
Awakened
DSM .456 .746 .275 .611 .542
PESTotal*DSM -.061 .181 .159 .340 .734

 

98

effects of the DSM on PASRD and health outcome variables entered into the regression
model (see Table 25).

The next phase of the analysis was to test the relationships between PASRD, DSM
and Health Outcomes and to determine if DSM acted as a moderator in this relationship.
As in the previous interaction models the term PASRD*DSM was entered into the
regression model along with PASRD and DSM as a single term. There were no
signiﬁcant relationships found with the interaction term for each outcome variable
indicating that DSM did not act as a moderator on the relationships between PASRD and
health outcomes (see Table 26).

Question 11: What is the effect of Disease Self-Management Behavior on the
relationship between PASRD and Asthma Health Related Quality of Life?

The ﬁrst phase of the analysis was to run a regression for PASRD on AHRQOL. Results
indicated a signiﬁcant negative relationship between PASRD and AHRQOL, R2 = .109,
B = -.329, SE = .071, B = -.329, t = -5.50, p < .000.The second phase of this analysis was
answered in the previous question indicating a signiﬁcant relationship between PASRD
and DSM. In the third equation DSM failed to act as a signiﬁcant predictor of AHRQOL,
R 2 = .109, B = .011, SE = .041, B = .021, t = .253, p = .801 indicating that a mediation
model did not exist (see Table 27).

The next phase of the analysis of the relationships between PASRD, DSM and
AHRQOL was to determine if DSM acted as a moderator in this relationship. As in the
previous interaction models the term PASRD*DSM was entered into the regression
model along with PASRD and DSM as single terms. There were no signiﬁcant

relationships found with the interaction term for each outcome variable indicating that

99

DSM did not act as a moderator on the relationships between PASRD and QOL although
this relationship trended towards signiﬁcance p = .067, (see Table 28).

PASRD was found to be a predictor of QOL. Although it was anticipated that PASRD
would predict QOL the relationship was not anticipated to be a negative relationship. To
further understand this relationship hierarchical regression was run with all of the
predictor variables to determine their contribution to this outcome.

Using hierarchical regression each predictor variable was entered using an a
priori approach. Asthma severity was entered ﬁrst followed by diagnosis, PBS, and
PASRD. Results indicated that asthma severity (R = .488, R2 = .23 8, p < .000), followed
by PASRD (R = .546, R2 = .298, R2 change =.042, p < .000) accounted for the majority
of the variance explained (see Table 29). In order to determine if males and females
differed on the above relationships the analysis was run again using a split ﬁle technique
in hierarchical regression to determine if the relationships held among males and females
separately. Results indicated that PES was a signiﬁcant variable in the model for males

but not females and that PASRD was signiﬁcant for females but not males (see Table 30).

100

Table 23

Regression Analysis of the Moderation Effect of DSM on the Relationship between PBS
and QOL

 

 

1v DV R B SE 13 t p-value
PESTotal QOL .122 -.098 .280 -.047 -349 .728
DSM -252 .246 -.511 -1.02 .307

PESTotal*DSM .050 .060 .441 .844 .400

 

101

Table 24

Regression Analysis of the Main Effect of PASRD on Health Outcomes

 

 

IV DV R B SE B t p - value

PASRD Numervis .152 .317 .120 .152 2.64 .009
Numhosp .070 .104 .098 .070 1.06 .290
Symptom
Days .102 .593 .333 .102 1.77 .076
Activity
Affected .138 .862 .359 .138 2.40 .017
Nights
Awakened .128 .610 .274 .128 2.22 .027

 

102

Table 25

Regression Analysis for the Mediation Effect of DSM on PASRD and Health Outcomes

 

 

IV DV R B SE B t p - value

Model 1

PASRD Numervis .106 .131 .208 .049 .629 .530

DSM .081 .079 .080 1.01 .312

Model 2

PASRD Activity .199 .831 .487 .130 1.70 .090
Affected

DSM .287 .186 .118 1.54 .123

Model 3

PASRD Nights .095 .389 .380 .079 1.025 .307
Awakened

 

103

Table 26

Regression Analysis for the Moderation Effect of DSM on the Relationship between
PASRD and Health Outcomes

 

 

IV DV R B SE [3 t p - value

Model 1

PASRD Numervis .108 .199 ..320 .075 .621 .536

DSM .128 .189 .127 .680 .497

PASRD*DSM -.019 .067 -.064 -.279 .780

Model 2

PASRD Activity .219 1.52 .733 .230 2.08 .039
Affected

DSM .800 .444 .328 1.80 .073

PASRD*DSM -.197 .155 -.279 -1.27 .206

Model 3

PASRD Nights .095 .419 .574 .085 .730 .467
Awakened

DSM .086 .348 .046 .246 .806

PASRD*DSM -.008 .121 -.015 -.069 .945

 

104

Table 27

Regression Analysis for the Mediator Effect of DSM on the Relationship between
PASRD & QOL

 

 

IV DV R B SE B t p - value
PASRD QOL .270 -.347 .105 -.277 -3.29 .001
DSM .011 .041 .021 .253 .801

 

105

Table 28

Regression Analysis for the Moderator effect of DSM on the Relationship between
PASRD & QOL

 

IV DV R B SE B t p - value
PASRD QOL .306 -.571 .161 -.456 -3.55 .001
DSM -.146 .094 -.295 -1.54 .124
PASRD
*DSM .062 .034 .438 1.84 .067

 

106

Table 29

Hierarchical Regression for Predictors of QOL

 

 

Model R R2 Change in Rf Sig. F Change
Step 1 .488 .238 *** .000
Severity
Step 2 .499 .249 .012 .058
Diagnosis
Step 3 .507 .257 .008 .122
PESTotal
Step 4
PASRD .546 .298 .042 .000

 

107

Table 30

Hierarchical Regression for Predictors of QOL by Gender

 

 

Model R2 Change in R2 Sig. F Change

Step 1

Severity

Male .478 .229 *** .000

Female .504 .254 *** .000

Step 2

Diagnosis

Male

Female .488 .238 .010 .317
.518 .268 .014 .092

Step 3

PESTotal

Male .551 .304 .066 .008

Female .522 .273 .005 .304

Step 4

PASRD

Male .572 .327 .023 .105

Female .570 .325 .052 .001

 

108

Chapter 5
DISCUSSION

Asthma is a common disease among urban adolescents yet little is known about the
unique needs of this group in terms of factors that inﬂuence asthma self-regulation
development, disease self-management, health outcomes and asthma health related
quality of life. The unique needs of adolescents are often neglected due to the fact that
they are generally studied collectively with children or adults. Adolescence is a period of
signiﬁcant cognitive, physical, social and emotional development. During this time in life
youth are transitioning from childhood into adulthood. An understanding that this period
of life is characterized by developmental grth and transition begs for separate studies
to identify the unique needs of adolescents.

If not properly managed, asthma can be life threatening (ALA, 2005). Although deaths
due to asthma are rare among children, the frequency of asthma related deaths increases
with age (ALA, 2005). Adolescence is a period of declining disease self- management
behavior. Poor disease self-management is related to poorer disease control which places
adolescents at greater risk for disease related morbidity, and mortality. Further potential
life long behaviors for disease management are established during adolescence. Therefore
it is essential to understand factors that positively inﬂuence disease self-management
during adolescence in an attempt to establish effective life long behaviors that achieve
positive health outcomes and that promote asthma health related quality of life.

The primary goal of this cross sectional, correlational study was to examine the
relationships between perceived emotional support, phase of asthma self-regulation

development and disease self-management behavior among urban adolescents with

109

asthma. Additionally the study sought to determine if PES, PASRD, and DSM were
directly or indirectly associated with health outcomes and asthma health related quality of
life. This study extended previous research of adolescents with asthma in that it focused
speciﬁcally on urban adolescents and because the factors identiﬁed to inﬂuence disease
self-management behavior have not previously been studied among this population.
Predictor Variables

PES represented one of the social support functions as an environmental factor within
the proposed model for this study. Social support has been identiﬁed as important to
developing youth and their success as they assume greater responsibility for DSM.
However, the efﬁcacy of the speciﬁc support function varies depending on the behavior.
PBS was considered to be relevant due to the age of the study participants being a period
of transition when youth assume primary responsibility for DSM. Also sources of support
such as parents, friends, and social contacts are the most inﬂuential persons in the
adolescent’s social environment.

Among the participants in the study PES scores were at the higher end of the scale
indicating greater perceived support. This ﬁnding does not compare directly with other
populations that have been studied using the same scale as the range of responses in the
current study were modiﬁed ﬁom 1-7, to 1-5, however general comparisons can be made.
When the unmodiﬁed Multi-dimensional Scale of Perceived Social Support (response
range 1-7) was administered to healthy urban adolescents (Canty-Mitchell & Zimet,
2000) the means were similar to ﬁndings in the current study in that they indicated a
higher perception of emotional support and the ranking of the highest mean score to the

lowest mean score followed the exact same pattern in both studies. The current study

110

extends what is known regarding PBS in that the instrument has now been used in an
adolescent population with a chronic disease and the results are similar to a healthy urban
population with special person being highest followed by ﬁiends and then family. The
similarities in scores and the pattern in scores may indicate that there is no difference
between healthy urban adolescents and urban adolescents with asthma in terms of their
global perception of emotional support.

Gender differences on the PES variable were found to be signiﬁcant. The scores of
males were signiﬁcantly lower than females for total support and each subscale except
family support. The gender variation is similar to studies of adolescents with diabetes
where females perceived greater general and disease speciﬁc emotional support than
males ﬁ'om ﬁiends (La Greca et al. (1995); Skinner, John, & Hampson, 2000). According
to Barbee et al. (1993) gender differences likely represent the stereotypical differences
that characterize females as being more socially skilled, emotionally sensitive,
expressive, and concerned with personal relationships than males. Differences between
males and females must be considered when developing interventions to promote
emotional support from sources other than the family. Evidence from the current study
and the studies cited indicate that emotional support may be more relevant for males and
may require enhanced or different strategies than those designed for females when
support is from sources other than familial.

A poorer perception of emotional support raises concerns regarding adolescent males
in general and more speciﬁcally those with a chronic disease such as asthma. Poorer
perceptions of emotional support especially ﬁ'om ﬁiends could place males at higher risk

for negative health outcomes as well as higher risk behaviors such as smoking which has

111

negative health consequences for asthmatics. During adolescence youth are known to
gradually gravitate towards ﬁiends and away from parents, a relatively stable source of
emotional support. For males this may be a transition that is more unstable than for
females and may contribute to isolation, depression and high risk behaviors. This raises
considerable concern as youth who engage in high risk behaviors are less likely to engage
in disease self-management.

The ﬁnding that PES did not differ by gender when family was the source may
represent the stability of the family relationship that is well established prior to
adolescence. Such a hypothesis is supported in a study by Shroff Pendly et al. (2002) who
found that when the mean of perceived family support was compared between children
(8-12yrs) and adolescents (13-17 yrs) there were no signiﬁcant differences. This ﬁnding
could also indicate that provisions of emotional support are not gender speciﬁc within
families. An awareness that PES from families is perceived similarly between males and
females informs researchers that interventions to enhance emotional support from
families for urban youth need not be gender speciﬁc.

The PES variable was also analyzed to determine if the source of support was
signiﬁcantly different among adolescents. Means of the Family and Friends subscales
were not signiﬁcantly different. In contrast the Special Person subscale was signiﬁcantly
different than family and ﬁiends subscales. This ﬁnding is similar to the results ﬁom the
study by Canty-Mitchell & Zimet, (2000). Despite the fact that the sources special person
differs from the other subscales, there have been no known published studies that identify
who the special person represents. Special person may overlap with friends or family

members, but the individual may count on one family member such as the mother and

112

consider her as having an additional or special role above and beyond that considered
within the familial role. Additional research is needed to clarify who the Special Person is
that adolescents identify as a source of emotional support.

PES &. DSM

Once the PES variable had been fully analyzed the next step was to determine if there
was a direct effect on DSM. In the current study there was no relationship between PBS
and DSM. These ﬁndings differ from a study of Aﬁican American adolescents with
asthma from a southern state, where participants with greater social support reported
greater disease self-management (Sin et al., 2005). The studies are similar, but not
equivalent in that in the Sin, et al. (2005) study, the type of support studied was a global
measure of support not emotional support, and disease self-management was measured
using a 27 item questionnaire as compared to a single item. However, the comparison is
made to point out how the relevance of support function (perceived emotional support vs.
affect, afﬁrmation, and aid or tangible support) may vary in association with the selected
outcomes.

PES has been studied among adolescents with diabetes for associations with disease
self-management behavior. Within this population, PBS was not related to tasks such as
insulin administration or blood glucose testing which are considered key tasks in diabetic
self-management. Instead PES ﬁ'om family was oriented toward praise, and
encouragement of self care efforts, conveying a sense of acceptance, and helping
adolescents maintain a positive outlook on their diabetes (La Greca, 1995). PES from
ﬁiends was primarily oriented towards helping the adolescent feel accepted and showing

sensitivity to the adolescent’s feelings about having diabetes.

113

There are several hypotheses that could explain the failure to ﬁnd an association
between PBS and DSM in the current study. One of the reasons this relationship was not
demonstrated in the current study may be that it does not exist. Of the studies reviewed in
the literature that focused on adolescents and perceived emotional support, none were
found that demonstrated a relationship with disease self-management behavior. Another
point to consider is the variability in social support function (emotional, instrumental,
informational and appraisal) and its association with disease self-management. Youth
may ﬁnd emotional support beneﬁcial and important, but this type of support may not be
related to implementing a task, as much as it may be related to maintaining a positive
attitude about having asthma. In a qualitative study of adolescents with asthma, Knight,
(2005) found that adolescents that had adequate social support did not identify feelings of
shame, or feeling different when using inhalers in school or sports. La Greca et al. (1995)
suggest that diabetic adolescents that have inadequate sources of emotional support
(speciﬁcally ﬁom friends) may feel uncomfortable telling their ﬁiends about their disease
and these same youth may also lack and important support resource for diabetes care. In
the current study emotional support was measured as a global form of support, it is not
clear if a disease speciﬁc form of emotional support would have yielded different results.
Further 32% of the study population did not have a diagnosis of asthma and therefore
although they carried an inhaler and used it for respiratory symptoms they may not
associate medication use with the diagnosis asthma Finally having a single item to
represent DSM was inadequate. Individuals with asthma must implement a number of

activities, all of which fall under the heading of DSM. In the current study, only one of

114

the task related activities was identiﬁed and this may have been insufﬁcient to fully
represent the concept.
PES Health Outcomes & Asthma Health Related Quality of Life

The study model depicts indirect relationships between PES, and health outcomes and
between PBS and AHRQOL. The indirect relationships were hypothesized as being
mediated by DSM. As an initial step in testing a mediator relationship, analysis for direct
relationships are tested. There were no direct relationships between PBS and any health
outcomes or AHRQOL therefore a mediation model could not be tested.

Some variables may act as a mediator or a moderator depending on the theory being
tested (Frazier, Tix & Barron, 2004). In the current study DSM could potentially be
conceptualized as a moderator variable in part because of the lack of evidence against this
association. If this were the case this ﬁnding would suggest that PES interventions would
vary in effectiveness based on the level of DSM. Altemately, according to Cohen &
Cohen, (1983) this relationship is symmetrical meaning the level of the independent
variable could also explain the association. However analysis did not show an interaction
effect of DSM and PES on Health outcomes or AHRQOL.

PASRD & DSM

The second predictor variable of DSM was phase of asthma self-regulation
development. Persons that are diagnosed with asthma are hypothesized to transition
through 4 phases of self-regulation that begin with acceptance of the diagnosis of asthma
followed by the progressive and sequential development of thought processes to manage
asthma proactively. Phase of asthma self-regulation was hypothesized to act as a

mediator in the relationship between PES and DSM. However after determining that PES

115

was not a signiﬁcant predictor of DSM, steps were taken to evaluate PASRD as a
moderator. Theoretically, PASRD could act as a moderator as this concept is represented
by 4 different phases. In the current study PASRD was found to act as a moderator in the
relationship between PBS and DSM (see Figure 2).

As a moderator PASRD acts as an independent variable that affects the strength and
or direction of the association between PBS and DSM. According to Chmura, Wilson,
Fiairburn, & Agras (2002) as a moderator PASRD acts to identify on whom and under
what circumstances treatments have certain effects. Prior to testing for the moderation
affect, a MANOVA was conducted and the mean scores for PES were consistently
highest at phase IV and lowest at phase II. This ﬁnding supports the potential effect of a
moderator in which PES is predictive of DSM depending on the phase of asthma self-
regulation. The moderation effect of PASRD on the relationship between PBS and DSM
was also found to be signiﬁcant. These results may also indicate that other forms of
support such as instrumental or informational support are effective depending on the
phase of self-regulation development. Further investigations are warranted to study this
relationship as no known published studies exist for comparison of ﬁndings.

Another hypothesis that may explain the moderator effect of PASRD is that as the
individual becomes more knowledgeable and is progressively able to plan how to handle
the day to day observation, judgment and evaluation associated with asthma self-

regulation emotional support may be more important for maintenance of self-regulation

116

Figure 2. Moderator Model of PBS and DSM

 

 

V

Perceived Emotional # Disease Self-Management
Support Behavior

 

 

 

 

 

 

 

 

Phase of Asthma Self-
Regulation Development

 

 

 

than for development of self-regulation. Phase 4 is described as the period when support
is withdrawn as the adolescent becomes increasingly self-regulating (Clark, &
Zimmerman, 1990). The ﬁnding is also consistent with discussions by Clark and
Zimmerman (1990) who describe the need for various “social and physical support” that
should be introduced during the learning and instructional phase of self-regulation
development that is ultimately withdrawn over time.

The literature is void of evidence from scientiﬁc studies of factors that inﬂuence the
progression of youth with asthma through the phases of self-regulation. The current study
adds to the scientiﬁc body of knowledge by identifying descriptive ﬁndings of urban
adolescents and PASRD as well as exploring associations between PASRD and an
environmental factor (PBS) and behavior (DSM).

PASRD, DSM, Health Outcomes and AHRQOL

During the next phase of analysis, direct relationships between PASRD and Health

Outcomes, and PASRD and AHRQOL were examined. These steps were taken prior to

testing a mediation model with DSM acting as a mediator. PASRD was found to have

117

direct effects on number of emergency department visits, days activities were affected
and nights awakened due to asthma. These results are similar to ﬁndings by Zimmerman
et a1. (1990) which were discussed previously. In the analysis of the direct effect of
PASRD on AHRQOL, a negative relationship was found. This was not anticipated as
intuitively and ﬁom a theoretical perspective one would expect that as one progressed
through the phases of asthma self-regulation development, that health related quality of
life would improve. Therefore, additional analyses were conducted to explore factors that
might explain these ﬁndings. The results are discussed later.

Next the mediation model was tested for the variables predicted by PASRD. None of
the models were found to be signiﬁcant. Again once the mediation model was found
insigniﬁcant the moderation model was tested. The moderation model also failed to
demonstrate a signiﬁcant interaction between PASRD and DSM on the outcomes
identiﬁed.

According to Clark et al., (2001) disease self-management strategies are goal driven.
Each of the different outcomes evaluated would be expected to represent different goals
by the adolescent. In other words some adolescents may have a goal of minimizing
emergency department visits, where as others may have a goal of increasing the number
of days for which they experience fewer activity restrictions. Each goal would also likely
represent different disease self-management behavior to the adolescent. Representing
DSM by one item limited the opportunity to detect different behaviors that adolescents
use to achieve the outcomes of interest. Also the cross sectional design of the study is
representative of the individual’s state of self-regulation at one moment in time. PASRD

is hypothesized to be a sequential process that is developed over time. Therefore, a

118

longitudinal study could yield different results. Additional investigations are necessary to
further understand the relationships hypothesized in the current study as well as the study
results.

PASRD & AHRQOL

The relationship between PASRD and AHRQOL was tested using a regression model
and found to be negative. This relationship has not previously been tested in the
literature. Theoretically, as one develops self-regulation skills morbidity and mortality
might be minimized and therefore AHRQOL would improve. Hierarchical regression was
used to identify the variables within the study that contributed most to the relationship
between PASRD and AHRQOL. Findings indicated that Asthma Severity explained 23%
of the variance. In the ﬁnal model there were signiﬁcant negative relationships between
severity and PASRD with AHRQOL and a signiﬁcant positive relationship between PES
and AHRQOL.

National guidelines deﬁne asthma severity by self report of the frequency of asthma
symptom experience in addition to objective measures of airway obstruction. In the
current study symptoms such as cough and wheeze, activity restrictions and night time
awakenings did not vary between persons with a diagnosis of asthma and those without.
Within the regression model there was no relationship between diagnosis and AHRQOL.
Therefore, ﬁndings that disease severity is negatively related to AHRQOL has far
reaching implications.

Limitations
Although this study offered insight into factors hypothesized to inﬂuence DSM,

Asthma Health Outcomes and AHRQOL there are limitations in terms of implications

119

and interpretation of the results that must be acknowledged. There are both design and
methodological ﬂaws that contribute to the limitations of the study. Urban Aﬁican
American adolescents were the population of interest for this study. This population has
been described as having a greater prevalence of asthma and greater morbidity and
mortality experiences when compared to their Caucasian counterparts. Adolescence also
represents a unique transitional period of life when social, physical, cognitive and
emotional changes differentiate them from children and adults. Also having a greater
understanding of factors that may affect morbidity and mortality and potentially the
related cost of care further supported the decision for the selected population. However,
due to the unique socioeconomic characteristics of the study population and difference
between adolescents, adults or children, the study ﬁndings cannot be readily generalized
to other populations.

The cross sectional design was selected for the study, as adequate research regarding
the variables of interest among urban Aﬁican American adolescents is limited. Due to the
limited existing knowledge the study was designed to primarily describe what was not
already known. Although the reported results included inferential statistics these ﬁndings
are not suggested to implicate causality which would require a longitudinal experimental
design. Further when reporting a negative relationship between variables the author can
only use theory to suggest the direction of each variable in an attempt to explain the
ﬁndings.

Measurement of several of the study variables may have also resulted in limitations on
both the analytical test that could be used as well as the ability to interpret results. The

MSPSS is a valid reliable instrument that measures a global perception of PES. However,

120

Social Support is multidimensional and perhaps would have been better represented by
studying more of the functions (instrumental, informational, appraisal) of this concept to
gain a greater understanding of how each function may have contributed to outcomes. In
the same vein, DSM is also multidimensional however in the current study a single item
was utilized to represent this concept. Disease self-management regimens prescribed for
adolescents are often complex and include administration of multiple medications,
avoidance of asthma triggers and use of peak ﬂow devices to monitor disease severity. In
the current study, the ﬁ'equency of carrying an inhaler was the only measure of DSM.
Although carrying and inhaler is an important part of DSM and is a recommendation that
should be carried out on a daily basis, this factor alone is inadequate to fully represent
DSM.
Implications

Findings ﬁ'om the current investigations have implications for clinical practice and
future research of factors that inﬂuence DSM. Despite the limitations related to the
exploratory focus of the study the results provide both new information and inferences
regarding relationships that may exist between study variables.
Clinical Implications

A holistic approach to the management of health problems includes the recognition of
factors beyond pathological processes which affect health outcomes and health related
quality of life. An important focus of holistic care includes counseling on health
behaviors that are implemented as a part of DSM. Counseling clients on health behavior
has been described as having promising potential towards disease prevention and

management (Glasgow et al., 2005). Although the current study ﬁndings will require

121

additional investigations before recommendations can be formalized the focus of study is
on factors that inﬂuence health behavior which could aid clinicians in the future to
positively impact health outcomes during clinic visits.

According to Clark, (2003)

The extent to which the person holds the requisite knowledge and beliefs to support
an action depends, in part, on a range of external factors. These may include role
models that can be observed making efforts in asthma situations: interpersonal
relationships through which emotional and instrumental social support is given and
received; and almost certainly , technical advice from a clinician who provides
therapeutic recommendations, p. 293).

Clark (2003) goes on to suggest that persons with a chronic disease may need assistance

to modify external factors in order to enhance ones ability to be self-regulating.

The clinician is in a key position to assess and provide assistance to clients through
acts such as counseling in order to help them become self-regulating. Studies such as the
current one and others will provide critical information on factors that the clinician must
address in order to effectively support self-regulation development and the associated
changes in health behavior. The traditional focus of disease self-management has been to
provide advice and recommendations that was guided by pathological mechanisms of
disease. Over time health outcomes have demonstrated that a broader approach to disease
management is necessary. This broader approach is inclusive of health behavior
counseling which must take into account social contextual factors that inﬂuence disease

self- regulation development and disease self-management behavior.

122

Treatment advice from clinicians to youth affected by asthma includes directions such
as follow an asthma action plan, avoidance of triggers and knowledge of how and when
to use medications. The most common means of assuring that youth achieve the targeted
treatment objectives is via education. Despite the clear evidence to support how essential
education is towards achieving health outcomes, there is an equal level of support that
clearly indicates education alone is inadequate. Clinicians such as Advanced Practice
Nurses (APN’s) are in a perfect position to assist youth by focusing on psychosocial
factors that provide the context for self-regulation development and disease self—
management. This proposed model of care would allow APN’s to explore the efﬁcacy of
using psychosocial factors to inﬂuence and or improve disease self-management behavior
in clinical practice.

The current study also adds to the scientiﬁc body of knowledge regarding the role of
emotional support and PASRD. As previously noted the study was not experimental in
design and therefore results are only inferential in nature. However ﬁndings suggest that
there is a relationship between PBS and PASRD, and that the relationship between PES
and DSM is moderated by PASRD. Clinicians must rethink current practices that for the
most part are void of services to address non-medical factors that could make a difference
in health outcomes that have yet to be achieved using traditional models of care.

PBS was found to be directly related with PASRD and PASRD was found to be
directly related to DSM. Because of the nature of these variables it is more difﬁcult to
demonstrate their effectiveness especially in a demographically and socioeconomically

diverse population. However, studies such as the current one are beginning to provide

123

evidence for the efﬁcacy of how psychosocial variables inﬂuence DSM which can be
used to inform clinicians of the value of addressing these issues in clinical practice.
Research Implications

Disease self management is complex and few gains have been made towards
providing scientiﬁc evidence of effective strategies to promote related behavior as well as
improve health outcomes. However of the studies that have reported successful programs
to enhance disease self-management many have been based on a theoretical
understanding of human behavior (Clark, 2003). The current study used a behaviorally
based theory to guide the selection of the variables included. Behavioral theory was also
used as the bases for the hypothesized relationships within the study.

Although there were noted limitations of the results related to the hypothesized
relationships in the study they cannot be considered a failure of the underlying theory.
The ﬁndings of the moderated relationships between PES, DSM and PASRD were weak,
but clinically and statistically signiﬁcant. Each variable is one that can potentially be
addressed during a clinic visit and that may contribute towards improving health
outcomes. The variables in this project had not previously been studied in the selected
population and ﬁndings can be utilized to inform future research. Therefore ﬁndings
should be considered as informative and additive to what is known about the study
population. Findings such as the role of gender in PES were found to be similar to
previous research. Also PASRD was negatively related to QOL and asthma severity

explained this relationship.

124

Conclusion

Urban adolescents with asthma face daily challenges of implementing disease self-
management behaviors that are essential to minimizing the risk of disease related
morbidity and mortality and enhancing asthma health related quality of life. These
challenges come at a time in life when normal developmental transitions are occurring
that make the needs of this population unique ﬁ'om children and adults. Although great
strides have been made in the scientiﬁc community regarding the complex physiological
pathways of airway inﬂammation, and hyperresponsiveness, little is known about the
equally complex environmental factors that inﬂuence asthma self-regulation, disease self-
management behavior, health outcomes and asthma health related quality of life.

There were a number of ﬁndings ﬁ'om this study that have been identiﬁed and
discussed in the results and discussion section of this paper. However the following will
serve to summarize these ﬁndings in a concise manner for the reader. First, the covariates
gender, diagnosis and severity each contributed to the ﬁndings in different ways. Gender
differences were only found for the variable PES. This ﬁnding is consistent with previous
research in healthy adolescents and in adolescents with a chronic disease. Results from
the current study of adolescents with asthma were similar to studies of perceived
emotional support among healthy adolescents and adolescents with diabetes. Adolescents
with a diagnosis of asthma carried their inhaler more ﬁequently than those without a
diagnosis. This ﬁnding alone is difﬁcult to interpret. Carrying an inhaler may have been a
result of having more persons with a prescribed inhaler among diagnosed adolescents.
Further investigation is needed to determine if persons without a diagnosis and with an

inhaler differed from the described population. A precautionary interpretation would be

125

that persons with a known diagnosis of asthma may engage in disease management
behaviors differently than persons whose respiratory symptoms are treated as an episodic
illness for which long term disease management is not appropriate. Persons without a
diagnosis may not have been offered the same directions/education regarding inhaler use
or the need to carrying the prescribed rescue inhaler at all times. Asthma severity was not
found to vary by gender. However differences were found when participants were
stratiﬁed by diagnosis. Seventy three percent of non diagnosed participants met criteria
for mild intermittent asthma. This ﬁnding is consistent with other studies where it has
been noted that persons with mild intermittent symptoms of asthma often go
undiagnosed.

Second, the environmental factor PES was found to be at the higher end of the scale
among adolescents with asthma. All PES subscales differed by gender except the family
subscale. When the subscales were compared to determine if they were different, the
special person subscale was different from family and ﬁiends. Findings on the PES
variable were similar to those reported on healthy urban adolescents. In future research of
PES investigators must plan to identify who the special person is among study
participants. Third, PBS was found to have a signiﬁcant relationship with PASRD. This
ﬁnding represented an original ﬁnding and has potential as a new line of inquiry. Fourth,
no relationship was found between PBS and DSM. This ﬁnding was consistent with
previous research among adolescents with diabetes. Fifth, no relationship was found
between PBS and Health Outcomes or AHRQOL. These relationships had not previously
been tested among urban adolescents with asthma and represent a new ﬁnding that must

be interpreted cautiously. Sixth, PASRD was found to be associated with DSM. This also

126

represents an original ﬁnding and an opportunity for a new line of inquiry. Seventh,
PASRD was found to act as a moderator between PBS and DSM. Again this is an original
ﬁnding and additional investigations are needed to validate results. Eighth, there was no
effect of DSM on the relationship between PES and Health Outcomes or PBS and
AHRQOL. This was an original line of inquiry and the results should be interpreted with
caution as with any ﬁndings that have not been replicated. Ninth, DSM had no effect on
the relationship between PASRD and Health Outcomes. This was an original line of
inquiry and again results should be interpreted cautiously especially due to the identiﬁed
limitations of the variable DSM as it was operationalized in the current study. The tenth
and ﬁnal contribution was the ﬁnding that the relationship between PASRD and
AHRQOL was negative. This was also an original ﬁnding and one that was unexpected.
Within the study the covariate asthma severity was found to explain this relationship.
This ﬁnding will inform future research efforts that will need to ﬁuther investigate these
ﬁndings.
Next Step

The “next step” is always a daunting task for researchers. Depending on the outcomes
of a study the next step may be explicitly clear or may require serious thought. In the case
of the current investigation the next step requires serious thought as there are a number of
paths that could be taken. This investigator believes that the next step towards developing
a research agenda that ﬂows from the current study is to maintain a focus on urban
adolescents with asthma. The morbidity and mortality among this population
demonstrates clear health disparities when compared to Caucasian counterparts yet

effective treatment options exist. Among urban adolescents disease self-management

127

behavior holds promise as a potentially effective means of inﬂuencing and improving
health outcomes and health related quality of life. Therefore future research will continue
to focus on factors that inﬂuence disease self-management.

In the current study only one function of emotional support was investigated. The
instrument tested was a global measure of emotional support and may not have been
sensitive to the needs of individuals affected by asthma. To better understand this
relationship it will be important to develop an instrument that is both reliable and valid in
measuring social support. Additionally the instrument should measure more than one
function of support and it should be disease speciﬁc. Measuring the different functions of
support would allow investigators to gain a broader understanding of the differences
between each function and how each ﬁrnction uniquely contributes to disease self-
management behavior.

Another factor to consider and include in future research is to adequately measure
disease self-management. Results from the current investigation raise concern regarding
the ﬁnding that self-regulation development was negatively correlated with asthma health
related quality of life. This ﬁnding could be indicative of implementation of DSM that is
ineffective. Ineffective DSM may result in consuming thoughts associated with self-
regulation that negatively affect asthma health related quality of life. A clearer
understanding of the multidimensional aspects of DSM will allow for a clearer
interpretation of results. Therefore a more comprehensive measure of DSM would be
adopted in future research.

Finally the use of a theoretical model to guide future research is essential. The model

used in the current research focuses on the relationships between the individual their

128

environment and behavior. The self-regulation perspective of SCT is centered on how
these factors inﬂuence the individual’s ability to process their thoughts and actions to
achieve disease control. According to Clark (2003) the affected individual should always
be at the center of chronic disease control efforts unless personal or situational factors
exist that alter the individuals ability to participate in disease self management.

The self-regulation perspective of SCT remains consistent with the future research
agenda of this investigator. Therefore this theoretical model will be used during the next
phase of investigation. The initial study focused on multiple variables as independent
factors as well as sources of inﬂuence on DSM, health outcomes and health related
quality of life. The future research will take a step back to assure that the variables of
interest are measured in a valid reliable manner that will better allow the investigator an
opportunity to determine their signiﬁcances in the study of disease self-management

among urban adolescents with asthma.

129

APPENDICIES

130

Lung Health Survey

The purpose of this survey is to learn more about the respiratory (lung) health and the health
behaviors of high school students. Some of the answers may not ﬁt your situation, but please
answer them as best you can. Some of the questions may seem like a repeat of other
questions, but please try to answer all, of them. Your answers to this survey will be kept
PRIVATE and will n_ot be shared with parents, teachers, or other school staff.

 

you are able to breathe).
* Please answer the following questions.

 

This survey is about your respiratory health (how well your lungs work and how well

 

1. Have you ever had wheezing or whistling in the chest

at any time?
2 Have you had wheezing or whistling in the chest in the
' lat—st
12 months?
3 Have you had wheezing or whistling in the chest
' WITHOUT A COLD in the last 12 months?
4 How many attacks of wheezing have you had in the last
' 12 months? [IF NONE, PUT 0]
5 In the last 12 months, how often, on average, has your
' sleeg been disturbed due to wheezing?
6 In the last 12 months, has wheezing ever been severe
' enough to limit your speech to only one or two words at
a time between breaths?
7 In the last 12 months, has your chest sounded wheezy
‘ during or after exercise?
8 In the last 12 months, have you had a dgy cough at
' night, agart from a cough associated with a cold or
chest infection?
9 Have you had tightness or heaviness in the chest in the

last 12 months?

131

[1] Yes [2] No

[1] Yes [2] No

[1] Yes [2] No

number of attacks

[1] Never awoken with
wheezing

[2] Less than 1 night per week

[3] One or more nights per
week

[1] Yes [2] No

[1] Yes [2] No

[1] Yes [2] No

[1] Yes [2] No

 

 

 

THESE NBI’T FEW QUESTIONS ARE ABOUT THE LAST 12 MONTHS ..... [FROM September
2002 or LAST SCHOOL YEAR to September 2003. IF THESE SITUA TIONS HAVE NOT
HAPPENED TO YOU, ANSWER Zero 10)

 

10- In the past 12 months, how many times did you go to number of times
the emergency room because of your wheezing,
coughing, chest tightness or chest heaviness or trouble
breathing?

11. In the past 12 months, how many times did you go to number of times
the doctor because symptoms like wheezing, coughing,
chest tightness or chest heaviness or trouble breathing
were getting worse?

12. In the past 12 months, how many times did you have to number of times
stay in the hospital overnight because of wheezing,
coughing, chest tightness or chest heaviness or trouble
breathing?

13. In the past 12 months, about how many times did you number of times
refill your prescription for a puffer or inhaler with
medicine you use to treat wheeze, cough, chest
tightness or trouble breathing? (These puffers may also
be called a rescue or quick relief medication, like
Albuterol or Ventolin.)

 

 

NOW THINKING ABOUT YOUR LAST SCHOOL YEAR OR IN OTHER WORDS, THE 2002-
2003 SCHOOL YEAR. PLEASE TELL US .......

 

14. During the last school year, how many days did you number of times
miss school for any reason?

15. During the last school year, how many days of school number of times
did you miss due to wheezing, coughing, chest
tightness/heaviness?

 

NOW THINKING ABOUT THE LAST MONTH OR THE LAST 30 DA YS....

16. In the last 30 days, how many days did you have number of times
wheezing, coughing, chest tightness or chest
heaviness?

17. In the past 30 days, how many days did you have to number of times

slow down or stop your activities because of
wheezing, coughing, chest tightness or chest

heaviness?
18. In the past 30 days, how many nights did you wake number of times

pp because of wheezing, coughing, chest tightness
or heaviness?

132

 

 

19.

20.

21.

22.

23.

24.

25.

In the past 30 days, how many days did you have to
change your plans because of wheezing, coughing,
chest tightness or heaviness?

In the past 30 days, how many days did you have to
take medicine because of wheezing, coughing, chest
tightness or heaviness?

In the past 30 days, how many days did you miss
school for any reason?

In the past 30 days, how many days of school did

you miss due to wheezing, coughing, chest
tightness/heaviness?

Do you currently have a job?

In the past 30 days, how many days of work did
you miss due to wheezing, coughing, chest
tightness/heaviness? [IF YOU DO NOT WORK, PUT
0]

Has a doctor or other health care provider ever told
you that you have asthma?

number of times

number of times

number of times

number of times

number of times

number of times

[1] Yes [2] No

 

 

NOW WE WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT SMOKING....THIS
INFORMATION WILL BE KEPT PRIVATE AND WILL NOT BE SHARED WITH OTHERS.

 

26.

27.

28.

29.

30.

31.

32.

33.

Have you ever tried smoking cigarettes, even 1 or 2
puffs?

On the days that you smoked in the last 30 days,
did you smoke more than 2 cigarettes on those
days?

How many cigarettes have you smoked in the last
30 days? [IF NONE, PUT 0]

How many cigarettes have you smoked in the last 7
days? [IF NONE, PUT 0]

How many cigarettes have you smoked in the last
24 hours? [IF NONE,PUT 0]

How many cigarettes per day do you USUALLY
smoke?

[IF NONE, PUT 0]

How old were you when you ﬁrst started smoking?
[CHECK BOX IF NEVER SMOKED]

Do you think that you may try smoking within the
next 6 months?

How many people that live with you smoke inside
your home? [IF NONE, PUT 0]

133

[1] Yes [2] No

[1] Yes [2] No

Number of cigarettes
Number of cigarettes

Number of cigarettes

Number of cigarettes

[ ] check here if
never smoked

years

[1]Yes [2]No [3]l=ma

current smoker

Number of persons

 

35. Which of the following people that live with you [1] mother (step or foster mother)
smoke? (Circle all that apply) [2] father (step or foster father)
[3] other adults (18 yr or older)
[4] other non-adults (less than
18)
[5] no one living with me smokes

 

 

HERE ARE MORE QUESTIONS ABOUT SMOKING. PLEASE ANSWER AS HONESTLYAS
YOU CAN. YOUR ANSWERS WILL BE KEPT PRIVATE. IF YOU ARE NOTA SMOKER,
CIRCLE THE LAST BOX (I AM NOTA SMOKER) FOR EACH QUESTION.

 

[1] Within 5 minutes
36- How soon after you wake up do you smoke your ﬁrst [2] 6-30 minutes
Cigarette?

[3] 31-60 minutes
[4] After 60 minutes
[5] I am not a smoker

37 Do you ﬁnd it difﬁcult not to smoke in places where [1] Yes
' smoking is forbidden (like church, at the library, in the [2] No
movies, etc?) [3] I am not a smoker
38 Which cigarette of the day would you hate most to [1] The ﬁrst one of the
' give up? (For example, the ﬁrst one in the morning? morning
The one after dinner?, etc.) [2] All others
[3] I am not a smoker
39 Do you smoke more often during the ﬁrst hours after [1] Yes
' waking than during the rest of the day? [2] No
[3] I am not a smoker
40 Do you smoke if you are so ill that you have to stay in [1] Yes
' bed most of the day? [2] No

[3] I am not a smoker

 

AND NOW, A LITTLE INFORMATION ABOUT YOU .....

41. How tall are you?
feet
inches
42. How much do you weigh?
pounds

134

 

Puff City Baseline
Section: Introduction
Intro Text (T1)
You have been invited to participate in this program because you are having asthma symptoms including
wheeze, cough, chest tightness, or shortness of breath. You may never have been TOLD that you have
asthma, but if you are having these symptoms, you may have asthma. And that is why we would like for
you to participate in this program.

When we ask you questions about "asthma" or "breathing problems," we are talking about when you
wheeze, cough, have chest tightness, or feel short of breath.

Before you start, we need to ﬁnd out what you are doing for your asthma or breathing problems now.
Asthma or breathing problems are handled differently by each person. In the end, answers to these
questions will help us to see if the program was helpful to you.

Some of the questions may not ﬁt your situation, but please answer them the best you can.
There are no right or wrong answers; it's whatever you think or actually do.

Your answers will be kept private. We will not share your answers with your parents, teachers or anyone
outside of the project.

If you have any questions or need computer assistance in completing this survey, please see the orientation
assistant (person wearing a blue button).
Section: Initial
Initial Assessment (T2)

First, please answer some general questions...

1. How old were you when you ﬁrst started having asthma symptoms including wheeze, cough, chest
tightness, or shortness of breath? (If you've had symptoms since you were born, put "0").AgeSymptomStart

0 number
VALID/F: isEmptyMgeSymptomStart) or answerWithinRange(AgeSymptomStart, 0, 20)
2. Has a doctor or health care provider told you that you have asthma?DoctorDiagnosis

Yes
No
Don't Know [DontKnow]

SKIP/F: isEmpty(DoctorDiagnosis) or DoctorDiagnosi == 'No'or 'DontKnow'

135

3. How old were you when a doctor or health care provider said that you have asthma? (If your answer is
when you were born, put "0")AgeParentTo/d

0 number

VALID/F: isEmptyMgeParentTold) or answerWithinRange(AgeParentTold, 0, 20)
Section: Effects of as@
past 30 dgvs (Past30Davs)

Symptoms of asthma include wheeze, cough, chest tightness, or shortness of breath. We'd like to know how
these symptoms have affected you. The next few questions are about your health during the past 30 days,
that is, since {date30DaysAgo()}.

4. During the past 30 days, how many days did you have asthma symptoms like wheeze, cough, chest
tightness, or shortness of breath?Past3 ODaysDays Wheezing

0 number
VA LIDIF: is ValidPast3 ODaysA nswer(Past3 ODaysDays Wheezing)

5. During the past 30 days, how many days did you have to slow down or st0p your activities because of
asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?Past3 0Dajr'sDaysAffectedA cti vi ti es

0 number
VA LIDIF: is V alidPast3 ODaysA nswer( Past3 ODaysDaysA ffectedA cti vities)

6. During the past 30 days, how many nights did you wake up because of asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath?Past3ODaysNightsA woken

0 number
VA L] D] F .' is V al idPast3 ODaysA nswer(Past3 ODaysNightsA woken)

7. During the past 30 days, how many times did you change your daytime or evening plans because of
asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?Pas t3 ODays Tim es Chan gedPl ans

0 number
VA LIDIF: is V alidPast3 ODaysA nswer(Past3ODays TimesChangedPlans)

8. During the past 30 days, how many days did you take any medicine for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath?Past3()DajsDays/lledicine

0 number

VA LID] F .' is Va lidPast3 ODaysA nswer(Past3 ODays Da ysMed i cin e)

136

9. Do you use your inhaler or puffer (like albuterol or ventolin) more than two times a
week?Puffer Two Tim es

 

0 Yes
0 No
CurrentJobOuerY
10. Do you currently have a job?(‘urrentJob
0 Yes
0 No
AsthmJaEffects

 

SKIPIF: isEmpty(Current./ob) or C urrentJob == 'No'

11. During the past 30 days, how many times did you miss work because of asthma symptoms like wheeze,
cough, chest tightness,,or shortness of breath?Past3ODaysMissed Work

0 number
VA LID/F: is ValidPast3ODaysA nswer(Past3ODaysMissed Work)

12. During the past 30 days, how many days did you miss school for ANY
reason?Past3 ODaysMiss edSchool

0 number

VALID/F: isEmpty(Past3ODaysMissedSchool) or answerWithinRange(Past30DaysMissedSchool, 0. 30)

13. During the past 30 days, how many days did you miss school because of asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath?Past3ODaysMissedSchoolAst/zma

0 number

VALID/F: isEmpty(Past3ODaysMissedSchoolAsthma) or
answerWithinRange(Past3ODaysMissedSchoolAsthma, 0, 30)

14. Is there a particular season or month when your symptoms like wheeze, cough, chest tightness, or
shortness of breath are worse?ParticularSeason Worse

0 Yes
0 No
0 Don't Know [DK]

WorseSeasonsSKIP/F: isEmptvIParticularSeason Worse) or ParticularScason Worse in ['No', ' m

137

15. Thinking about asthma symptoms like wheeze, cough, chest tightness, or shortness of breath, during
what season or month are your symptoms worse? (Choose all that apply.) WorseSeasons

Fall (Sep, Oct, Nov) [Fall]

Winter (Dec, Jan, Feb) [Winter]
Spring (Mar. Apr. May) [Spring]
Summer (Jun, Jul, Aug) [Summer]

WorseSeasonsDetailsSK/PIF: isEmptylWorseSeasong
LOOP: for aSeason in WorseSeasons

16. Thinking of a typical month (30 days) during {aSeason}, how many days would you have asthma
symptoms like wheeze, cough, chest tightness, or shortness of breath?NumDays.S‘ymptoms{(zSeason,I

0 number
VA LID/F .' isEmpty(NumDaysSymptoms{aSeason}) or answerWithinRange(NumDaysSymptoms{aSeason},
0, 3 I)
list 12 months (LastlZMonths)

l7. Asthma attacks, sometimes called episodes, are periods of worsening asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath.

These next few questions are about asthma episodes during the past 12 months. Try your best to remember.

18. During the past 12 months, how many asthma attacks or attacks of asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath have you had?Lastl 2MonrhsNumEpisodes

0 number

VA LID/F .' isEmpty(Lastl2MonthsNumEpisodes) or answer WithinRange(LastI2MonthsNumEpisodes, 0,
365)SKIPIF: isEmpty(Last12MonthsNumEpisodes) or LastIZMonthsNumEpisodes < I

19. During the past THREE (3) months, how many asthma attacks or attacks of asthma symptoms like
wheeze, cough, chest tightness, or shortness of breath have you had?Last3MonthsNumEpisodes

0 number

VALID/F: isEmpty(Last3MonthsNumEpisodes) or answerWithinRange(Last3MonthsNumEpisodes, 0, 93)
HadEpisodesSK/PIF: isEmptvILastl2MonthsNymEpisodes) or LastlZMonthsNymEpisodes < I

20. During the past 12 months, how many times did you have to stay overnight in the hospital for
worsening asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?NumHospitalOvernig/rts

0 number

VALIDIF: isEmpty(NumHospitalOvernights) or answerWithinRange(NumHospitalOvernights, 0, 365)
HospitalStgygSKlP/F: isEmptvINumHospitalOvernights) or NumHospitalOvernights < l
LOOP: for OvernightNum in HospitalOvernights

138

--- The next few questions are about your * {visitRecency(Overnightl\lum)} * overnight stay in the hospital.

21. What was the date of your {visitRecency(OvernightNum)} hospital overnight stay? It's okay to
estimate. Do the best you can.HospitalOvernigh!Date{0verniglitNum)

0 (response group)
22. How many nights did you stay in the hospital?HospitalOvernightNumNig/zts ,"O\-'ernig/1thmz }
0 number
23. Were you in the Intensive Care Unit (also known as the ICU)?HospitalOt-’erniglztl C U ,’ Overnight/Vim: /

0 Yes
No
0 Don't know [DK]

24. Within two weeks after this hospital stay, did you see your regular doctor for a followup
appointment?H osp 1' ml Overn i gh tDidScheduleF o Ilowup ,’ Overn i ghIN um )

0 Yes
0 No
0 Don't know [DK]

ICUVisitsUSE/F: NumHospitaIOverniglzts < I or NumIC U Visits < I
25. Have you ever been in the Intensive Care Unit (also known as the ICU)?E1:‘er/n l C‘ U

0 Yes
0 No
0 Don't Know [DK]

ERVisitsOuerY

26. During the past 12 months, how many times did you make a visit to the emergency room (ER) because
of worsening asthma symptoms like wheeze, cough, chest tightness, or shortness of breath??NumER Visits

0 number

VALID/F: isEmptyWumER Visits) or answer WithinRange(NumER Visits, 0, 365)
ERVisitDetailsSK/PIF: isEmptv{NumER Visits) or NumER Visits < I
LOOP: for ER V isitNum in ER VisitsList

--— The next few questions concern your * {visitRecency(ERVisitNum)} * emergency room visit «-

27. What was the date of your {visitRecency(ERVisitNum)} visit? It's okay to estimate. Do the best you
can.ERDate{ER V isitNum }

0 (response group)

139

28. Which of the following Emergency Rooms did you go to?ERName,’E R Visithun ,1

Emergency room at Children's Hospital [CHM]

Emergency room at Henry Ford Hospital [HFHS]

Emergency room at St. John's Hospital [StJohns]

Emergency room at Detroit Riverview Hospital [DetRiverview]
Emergency room at Sinai Grace Hospital [SinaiGrace]
Emergency room at Detroit Receiving Hospital [DetReceiving]
Some other Emergency room [Other]

Don't know [DK]

29. Were you admitted to the hospital to stay overnight?E RA (Imitted{E R VisitNum )

0 Yes
0 No

30. Within two weeks after this visit to the emergency room, did you see your regular doctor for a followup
appointment?E RScheduledF ollo wup { E R l-"isithmi ,1

0 Yes
0 No
0 Don't know [DK]

DoctorVisits

31. Not including hospitalizations or emergency room visits, how many times during the past 12 months
have you seen ANY doctor FOR ANY REASON?Lastl 2MonthsDoctor V isitsA n yReason

0 number

VA LID/F: isEmpty(LastI 2MonthsDoctor V isitsA nyReason) or
answer WithinRange(Last1 2MonthsDoctor V isitsA nyReason, 0, 3 65)

32. Not including hospitalizations or emergency room visits, how many times during the past 12 months
have you seen a doctor for asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?Lastl2MonthsDoctor V isitsA sthma

0 number

DoctorDetailsSK I PIF .' isE mptv( Last] 2MonthsDoc-tor V isi tsA sthma) or Last/2MonthsDoctor V isitsA sth ma

140

33. Was this your regular family doctor or do you see this doctor ONLY for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath?DocrorReguIarOrAsthmaOnly

o I see this doctor ONLY for asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath. [AsthmaOnly]

o I see this doctor for EVERYTHING including asthma symptoms like wheeze, cough, chest
tightness, or shortness of breath. [OtherReasons]

0 Don't know [DK]

SpecialistQuervS K IPIF .' isEmptﬂLastl 2MonthsDoc-tor V is itsA sthma ) or Last] 2MonthsDoctor V isitsA sthma

During the past 12 months, have you seen any of the following specialists for asthma symptoms like
wheeze, cough, chest tightness, or shortness of breath?

Don't Know
Yes No [DK]

34. An allergist? Last] 2./lrI0nth/1]l(’l'ngI
35. A pulmonologist? Last] 2MonthsPulmono/ogist

36. A lung or breathing specialist?
Last I 2M0nthsLungSpecia/ist

37. Some other specialist for asthma symptoms like
wheeze, cough, chest tightness, or shortness of
breath? Last] 2MonthsOtherSpecialist

38. When was the last time you saw this doctor?LastTimeSawDoc-toi-Month
o ﬁllin
Last TimeSa wDoctor Year

0 ﬁllin

Section: Equipment
Equipment (Equipment)

These next few questions are about the instructions you have received about managing your asthma or
breathing problems.

37. How easy is it for you to follow the doctor's instructions about using your prescribed medicine for
asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?H owE as y TOP 0110 wDoctor/nstructions

1- Very easy [1]

2

3- Fairly easy [3]

4

5- Not easy at all [5]

141

0 I do NOT take prescribed medicine for wheeze, cough, chest tightness, or shortness of breath.
[DontTake]

SKIP/F: isEmpty(HowEasyToFollowDoctor/nstructions) or HowEasyToFolIowDoctorInstructions ==
'DontTake'

38. Do you usually follow your doctor's instructions for taking your prescribed medicine for asthma
symptoms like wheeze, cough, chest tightness, or shortness of breath? UsuallyFol/oit-ilnstructions

0 Yes
0 No

39. Do you use a spacer device with your puffer or inhaler? (A spacer is a separate device that catches the
mist from the puffer or inhaler.)UseSpacer

Yes

No

Don't Know [DK]

I do NOT have a puffer or inhaler. [DontTake]

M
USE/F: UseSpacer == 'Yes'

40. What type of spacer do you have? TipeSpac-er

Type A [TypeA]

Type B [TypeB]

I have both types [Both]
Don't Know [DK]

USE/F: UseSpace == 'Yes'

41. When was the last time you used the spacer?LastUsea'Spacer

Within the past 2 weeks [WithinZWeeks]
Within the past 2 months [Within2Months]
Within the past 12 months [Within12Months]
More than 12 months ago [MoreThaanMonths]
Don't Know [DK]

42. Do you have a peak ﬂow meter? (This is a device that shows how hard you can blow air out of your
1ungs.)HasPeakFlowMeter

0 Yes
0 No
0 Don't Know [DK]

142

PeakFlowMeterInfo
USE/F: HasPeakFlowMeter == 'Yes'

43.When was the last time you used the peak ﬂow meter?LastL.J’s'e(1'PeakF lowMetcr

Within the past 2 weeks [Within past 2 weeks]
Within the past 2 months [Within past 2 months]
Within the past 12 months [Within past 12 months]
More than 12 months ago

Don't Know [DK]

Some people carry their puffers or inhalers around with them, and some don't. Please tell us...
44. How often do you take your puffer or inhaler with you wherever you go?lnhalerWherever

I carry it or have it with me everyday. [EveryDay]

I carry it or have it with me most days. [MostDays]

I carry it or have it with me only on some days. [SomeDays]

I usually don't carry it or have it with me. [U suallyNoCarry]

I never carry it or have it with me. [N everCarry]

I don't have a puffer or inhaler for asthma or breathing problems. [DontHave]

Thinking about the past seven days...

45. How many days was your asthma inhaler or puffer near enough for you to be able to get to it quickly in
an emergency?Last 7 Da} '5 H 0 WM a n yDa ysl nhal erN ear

0 number

VALID/F: isEmptj/(Last7DaysHowManyDays/nhalerNear) or
answerWithinRange(Last7DaysHowManyDays/nhalerNear, 0, 7)

Section: Knowledge
Knowledge (Knowledge)

46. Do your teachers or any other school staff know that you have asthma or asthma symptoms like
wheeze, cough, chest tightness, or shortness of breath?Know Teachers

Yes

No

Don't Know [DK]

I have never been told that I have asthma. [NeverTold]

47. Has a doctor outlined an asthma care plan for you that advises you on what to do in case you have
asthma symptoms like wheeze, cough, chest tightness, or shortness of breath?KnowAsthmaCareP/an

0 Yes
0 No

143

48. Has a doctor outlined an asthma care plan for you that advises you on what to do in case you are
exposed to things that could cause you to have an attack of asthma symptoms like wheeze, cough, chest
tightness, or shortness of breath?KnowExposedCareP/an

0 Yes
0 No

49. Do you ever worry that you may not able to get to the doctor or hospital in time to get the care you need
for an attack of asthma symptoms like wheeze, cough, chest tightness, or shortness of breath?K now Worry

- Yes
0 No
0 Don't Know [DK]

50. Do you feel that asthma symptoms like wheeze, cough, chest tightness, or shortness of breath can be
life threatening if nothing is done to treat it?KnowLife Threatening

0 Yes
No
0 Don't Know [DK]

51. Do you have any special method to check for early signs of an oncoming attack of asthma symptoms
like wheeze, cough, chest tightness, or shortness of breath?KnowEarlySigns

0 Yes
0 No
0 Don't Know [DK]

SKIPIF: isEmpty(HowEasy ToFollowDoctor/nstructions) or HowEasy ToFoIlowDoctorInstructions = =
'DontTake'

52. Do you have any special procedure for observing changes in your symptoms after you take prescribed
medication for asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath?KnowObserveSymptom Changes

0 Yes
No
0 Don't Know [DK]

SKIP/F: isEmpIy(HowEasy ToFollowDoctorInstructions) or HowEasyToFollowDoctorlnstructions = =
'DontTake'

53. Do you have a systematic plan to adjust your medicine if asthma symptoms like wheeze, cough, chest
tightness, or shortness of breath get better or worse?KnowAdjustMedicineP/an

0 Yes
No
0 Don't Know [DK]

144

54. How much do you feel that your symptoms like wheeze, cough, chest tightness, or shortness of breath
restrict daily activities or prevent you from being able to do the things you would like to
do?KnowRestrictDailyActivities

- Very much [1]

MJBDJNH

- Not at all [5]

55. How serious can your asthma or breathing problem be?KnowScrious

1- Very serious [1]
2
3
4
5-

Not serious at all [5]

56. How important is it for you to have regularly scheduled appointments with the doctor for your asthma
or breathing problem?Knou'RegularAppointments

1- Very important [1]
2
3
4

5- Not important at all [5]
I have never seen a doctor for asthma or breathing problems. [N everSeen]

SKIP/F: isEmpty(HowEasyToFollowDoctor/nstructions) or HowEasyToFollowDoctor/nstructions ==
'DontTake'

57. How important is it to take all the medications at the exact dosage that the doctor has
prescribed?KnowEractDosage

1- Very important [1]
2
3
4
5-

Not important at all [5]

145

58. If the asthma medicine that the doctor prescribes does not seem to help your asthma symptoms like
wheeze, cough, chest tightness, or shortness of breath, how important is it to continue taking
it?KnowContinueMedicine

1- Very important [1]
2
3
4

5- Not at all [5]
I have never taken medications for asthma or breathing problems. [NeverTaken]

59. Do you know who to contact if you are having problems with your asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath?Know WhoContacr

Yes
No

SK IPIF .' isEmpty(HowEasyToFollowDoctor/nstructions) or HowEasy ToFollowDoctorInstructions = =
’DontTake'

60. Who is responsible for making sure you take your medication for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath the way your doctor recommended?PersonResponsible

My parents or guardian(s) make sure I take my medication the way the doctor recommended.
[Parents]

Some other adult besides my parent or guardian(s) makes sure I take my medication the way the
doctor recommended. [OtherAdult]

I, alone, am responsible for taking my medication the way the doctor recommended. [Self]

Both me and my parents/ guardians make sure I take my medication the way the doctor
recommended. [ParentsSelt]

61. Who helps you decide when medical care is needed for your asthma symptoms like wheeze, cough,
chest tightness, or shortness of breath? [check all that apply]Person Decides

Myself

Parent/ guardian [Parent]

Another adult (not that is not a parent/ guardian). [Other Adult]

I do not get medical care for asthma symptoms like wheeze, cough, chest tightness, or shortness of
breath. [DontGet]

146

Section: Doc and depression
Doc attention (DocAttention)

Here are some more questions about your doctor.
SKIP/F: isEmpty(PersonDecides) or PersonDecides == 'DontGet'

62. Some people hardly ever see the SAME doctor when they get medical care for their asthma symptoms
like wheeze, cough, chest tightness, or shortness of breath. Is this true for you?DocRarelySame

0 Yes
0 No

SKIPIF: isEmpty(PersonDecides) or PersonDecides == 'DontGet’

63. For some people, the breathing problems they have had in the past are IGNORED when they see a new
doctor for asthma or breathing problems. Is this true for you?DocHistory/gnored

0 Yes
0 No

Depression

64. Sometimes how we feel can affect our asthma or breathing problem. These next questions are about
how you have been feeling lately.

During the past 6 months, were there times when you were very sad?Dep6Months Velj‘Sad

0 Yes
0 Sometimes
No

65. During the past 6 months, has there been a time when you just weren't interested in anything and felt
bored or just sat around most of the time?Dep6MonthsBored

0 Yes
0 Sometimes
No

66. During the past 6 months, have you bad times when you felt that life was hopeless and that there was
nothing good for you in the future?Dep6M0ntthope/ess

Yes
Sometimes
No

147

67. During the past 6 months, were there times when you were grouchy or irritable, often in a bad mood, so
that even little things would make you mad?Dt’/)6:llmzt/zs Gram-12y

0 Yes
0 Sometimes
No

68. During the past 6 months, has there been a time when nothing was fun for you, even things you used to
likC?D(’p()./1'IOIIllIA'NUI/lIIIgFlm

- Yes
0 Sometimes
No

69. During the past 6 months, have you lost a lot of weight?[)ep/>.Iloin/is ling/111.0»;

0 Yes
0 Sometimes
No

70. During the past 6 months, have you been so down that it was hard for you to do your
schoolwork?Dep6.l 10 n t/szt Iron! 11 'or/t Hard

0 Yes
0 Sometimes
No

Please tell us if you agree or disagree with the following statements:
71. When under stress, I tend to pray, meditate, or work on my spiritual life.l)t’pRU/Igimt

Strongly disagree [StronglyDisagree]
Disagree

Neutral

Agree

Strongly agree [StronglyAgree]

72. Compared with others my age, I take I’lSkS.RL’/it’lRI.\/\'s

Strongly disagree [StronglyDisagree]
Disagree

Neutral

Agree

strongly agree [StronglyAgree]

148

73. I like to do things that bother my teaChCI'S.Rt'ltt’lb’UI/IUI‘

0 Strongly disagree [StronglyDisagree]
o Disagree

0 Neutral

0 Agree

0 Strongly agree [StronglyAgree]

74. I enjoy doing things that people say I should not d0.RUIN-‘lbllullltltlI

Strongly disagree [StronglyDisagree]
Disagree

Neutral

Agree

Strongly agree [StronglyAgree]

75. It is worth getting into trouble if I have ﬁln.Rt‘l)£:‘ll“IlII

o Strongly disagree [StronglyDisagree]
o Disagree

0 Neutral

0 Agree

0 Strongly agree [StronglyAgree]

social support (SocialSupport)

The following questions ask about ﬁiends, family and signiﬁcant others in your environment that may
provide you with emotional support.

Emotional support is your perception of feeling loved, valued, and special to others.

Respond to the following questions by thinking about how caring you feel others are as you experience the
challenges of living with asthma.
Strongly disagree Strongly agree
[StronglyDisagree] Disagree Neutral Agree [StronglyAgree]
76. There is a special person who is

around when I am in need.
SocSpecia/Pei'sonA round

77. There is a special person with whom I
can share my joys and sorrows.
SocSpec-falPersonJoysSorrows

78. I have a special person who is a real
source of comfort to me.
SocSpecia[Person Comfort

79. There is a special person in my life
who cares about my feelings.

$065ch in! Pcrso n F eel i rigs

149

80. The special person in my life I thought of when answering the previous questions was
a150c5pc'citt/Pcl'san

Relative

Friend

Teacher

Coach

Minister/Priest [Clergy]
Other

social support (FarnilySuppom

Now thinking about your family...
Strongly disagree Strongly agree
[StronglyDisagree] Disagree Neutral Agree [StronglyAgree]

81. I get the love and affection I need from

my family. SocFamili'LoveAf/ection

82. When I need support my family really

tries to help me. Soc/7 am ili'Sapport

83. I can talk about my problems with my

family. SocF am il t-‘C an Talk

84. My family is willing to help me make
decisions. SOCF am i/_1 ‘Dt’t‘ls ions

85. The family member I thought of most when answering the previous questions was
myzSor'Mai/I F am il tall ember

Mother

Grandmother [GMa]

Step Mother [StepMa]
Foster Mother [FosterMa]
Aunt

Father

Grandfather [GPa]

Step Father [StepPa]
Foster Father [FosterPa]
Uncle

Sister

Step Sister [StepSis]

Half Sister [HalfSis]
Foster Sister [FosterSis]
Brother

Step Brother [StepBro]
Half Brother [HalﬂBro]
Foster Brother [FosterBro]

150

social support (FriendSupport)

Now thinking about your friends...

Strongly disagree Strongly agree
[StronglyDisagree] Disagree Neutral Agree [StronglyAgree]

86. When I need support my friends really
try to help me. SocFriendsSupport

87. I can count on my friends when things
go wrong. SocFriends When Wrong

88. I have ﬁiends with whom I can share
my joys and sorrows.
So CF ri ends/0 ysS orro ws

89. I can talk about my problems with my
friends. SocF riendsC an Talk

90. The ﬁiends that provide me with the most support arezSocF riends Gender

0 Male
0 Female

91. I receive the most support ﬁ'om friends that are:SocFriemlsAge

0 Around my age [MyAge]
o A lot older than me [Older]
o A lot younger than me [Younger]

SocialSupportParents

92. Not including yourself, how many persons live with you now?NnmberHouse/mld

1 to 3 people [OneThree]

4 to 6 people [FourSix]

More than 6 people [MoreSix]

I live in a youth home, youth facility, or shelter. [YouthHome]

VALID/F: isEmpty(NumberHousehold)SKlP/F: isEmptleumberHouselzo/d) or NumberHousehold ==
'YouthHome'

93. Not including yourself, how many persons in your household less than 18 years of age have a diagnosis
of asthma?NumberUnderEighteen

0 number

VALID/F: isEmpty(NumberUnderEighteen) or answerWithinRange(NumberUnderEighteen, 0,
[00)SK1PIF: isEmpty(NurnberHousehold) or NumberHousehold == 'YoutliHome'

151

94. Not including yourself, how many persons in your household 18 years or older have a diagnosis of
asthma?NumberOverEighteen

0 number
VA LID/F .' isEmpty(NumberOverEighteen) or answerWithinRange(NumberOverEighteen, 0, [00)

Families work differently. Please tell us how your family does things...

Most of the Time
Never Rarely Sometimes [MostOfI‘heTime] Always

95. My parent(s) know where I am after school.
SocParentsKnowWhereAfterSchool

96. If I am going to be home late, I am expected
to call my parent(s) to let them know.
SocParentsExpectC all

97. I tell my parent(s) who I'm going to be with
before I go out. SocParents WhoGoOut

98. When I go out at night, my parents know
where I am. SocParentsKnowWhereGoOut

99. I talk with my parent(s) about the plans I have
with my friends. SocParentsPlans

100. When I go out, my parent(s) ask me where
I'm going. SocParentsAsk WhereGoOut

Section: Smoking
current smoking (CurrentSmoking)

These next few questions are about smoking. This information will be kept private and will NOT be shared
with parents or teachers. We are very serious about keeping your information private.

101. Which of the following best describes your current smoking?CurrentSmoking

I have never smoked [Never]

I have tried smoking a few times [F ewTimes]
I used to smoke regularly but I quit [Former]
I am a smoker [Smoker]

152

SmokingDetailsSK/PIF: C urrentSmoking == 'Never’
102. Have you smoked on one or more of the past 30 days?szveSmoked30Days

0 Yes
0 No

SKIP/F: HaveSmoked3ODays == 'No'

103. Did you smoke MORE THAN TWO cigarettes on any day during the past 30
days? TwoSmoked3 ()Days

0 Yes
0 No

SKIP/F: HaveSmoked3ODays == 'No'

104. How many cigarettes have you smoked during the past 30 days? [Estimate if you don't know exactly
how many].NumCigs30Days

0 number

VALID/F: isEmpty(NumCigs3ODays) or answerWithinRange(NumCigs3ODays, 0, 1200)SKIPIF:
HaveSmoked30Days == 'No'

105. How many cigarettes have you smoked during the past 7 days? [Estimate if you don't know exactly
how many] .N um C i gs 7 Days

0 number

VAL/DIP: isEme/(NumCigs 7Days) or answerWithinRange(NumCigs 7Days, 0, 280)SKIPIF:
HaveSmoked3ODays == 'No'

106. How many cigarettes have you smoked during the past 24 hours? [Estimate if you don't know exactly
how many].NumCigsZ4Hours

0 number
VALIDIF: isEmprleumCig524Hours) or answerWithinRange(NumCigsZ4Hours. 0. 60)
107. How old were you when you ﬁrst started smoking cigarettes?AgeStarrSmoking

0 number

VALID/F: isEmpty(AgeStartSmoking) or answerWithinRangeMgeStartSmoking, 5, 25)

153

108. During the past 30 days, how many days did you smoke marijuana (weed) or
b1unts?Marijuana3ODays

0 number
VALID/F: isEmpty(Marijuana3ODays) or answerWithinRange(Marijuana3ODays, 0, 30)

109. During the past 30 days, how many days did you smoke cigars, cigarillos, or little
cigars?Cigars3ODays

0 number

VALID/F: isEmpty(Cigars3ODays) or answerWithinRange(Cigars3ODays, 0, 30)
household smokers (HouseholdSmokers)

110. Thinking of the persons that LIVE WITH YOU, which of the following persons smoke? (Check all
that apply).HouseholdSmokers

Mother (including Foster or Stepmother) [Mother]
Father (including Foster or Stepfather) [Father]

Other adults (18 yrs or older) [OtherAdults]

Other non-adults (less than 17 years) [OtherNonAdults]
No one in my household smokes [NoOne]

111. Do you spend one or more nights per week in a household where someone smokes?SleepSmoker

0 Yes
0 No

SKIP/F: SleepSmoker == 'No'

112. Thinking of the past 30 days, that is since {date30DaysAgo()}, how many nights did you sleep in the
home of someone that smokes?SleepSmoker3()Days

0 number
VALID/F: isEmpty(SleepSmoker3ODays) or answerWithinRange(SleepSmoker3ODays. 0, 30)

113. Sometimes pets or pests found in the home can be related to breathing problems. Do you have any of
the following where you are living now? (Check all that apply).PestsHome

Cockroaches [Roach]

Mice or rats [Mice]

Dog

Cat

Other furry pets like a hamster, gerbil, or guinea pig [FurryPets]
Bird

154

114. Are you allergic to animals, molds, or pollen?.4llergic

0 Yes
0 No
0 Don't know [DK]

Section: PAOLO
Activities (Activities)

Because you have asthma, you may have found some of the things you like doing difﬁcult or not much ﬁrn.
Some people are bothered by asthma when doing some of the following activities.

115. Please check the box next to the THREE (3) things that have been bothered most by your asthma
during the past week These things must be activities that you do regularly. Q4 LA on" titles

Ball Hockey [BallHockey]
Baseball

Basketball

Dancing (Ballet / Jazz) [Dancing]
Football

Playing at recess [PlayRecess]
Playing with pets [PlayPets]
Playing with friends [PlayFriends]
Riding a bicycle [Bike]

Running

Jumping rope [JumpRope]
Shopping

Sleeping

Soccer

Swimming

Volleyball

Walking

Walking uphill [WalkHill]
Walking upstairs [WalkStairs]
Laughing

Studying

Doing household chores [Chores]
Singing

Doing crafts or hobbies [Hobbies]
Shouting

Gymnastics

Rollerblading / roller-skating [Roller]
Skateboarding

Track and ﬁeld [Track]
Tobogganing

Skiing

Ice skating [IceSkating]

Climbing

Getting up in the morning [GettingUpInMoming]
Talking

155

ActivitiesReduce USE IF: listCount(OA LA ctivities) > 3 S K I P] F .' isEmptleA LA ctivities)

Please choose only three activities.QA LA cavitiesReduced
. (response group)

IN VALID/F isEmpty (QALActivitiesReduced) or listCount(QALActivitiesReduced) > 3

 

LOOP: for A nA cavzty in QALActivities

Please tell us how much you have been bothered by doing these things during the past week because of
your asthma symptoms like wheeze, cough, chest tightness, or shortness of breath.

I- 4-
Extremely Somewhat 7- Not
Bothered Bothered Bothered

[l] 2 3 [4] 5 6 [7]

{activityDesc(AnActivity)}
QA LA cti vityBother,’ qalNum F orA ctlA nA c'tivity) } {A nA ctivity}

QALDetails
In general, how often during the past week did you:
4- 7-
1- All Some None
of the of the of the
time time time

[1] 2 3 [4] 5 6 [7]
116. Feel frustrated because of your asthma?
QA LFrus tra ted

117. Feel tired because of your asthma? QAL Tired

118. Feel worried, concerned or troubled because of
your asthma? QA L Worried

How bothered have you been during the past week by:

1- 4-
Extremely Somewhat 7- Not
Bothered Bothered Bothered

[1] 2 3 [4] 5 6 [7]
l 19. Asthma Attacks QA LAsthmaAttacks

156

In general, how often during the past week did you:

1- All
of the
time
[11 2
120. Feel angry because of your asthma?
Q4 l-Feel.‘l ngry

How bothered have you been during the past week by:

1-
Extremely
Bothered
11] 2
121. Wheezing Q4 L H hearing
In general, how often during the past week did you:
1- All
of the
time
[1] 2
122. Feel irritable (cranky/grouchy) because of your
asthma? QALlrritablc
How bothered have you been during the past week by:
1-
Extremely
Bothered
[l] 2
123. Tightness in your chest Q4 L( 711‘s!TIg/Imcss
In general, how often during the past week did you:
1- All
of the
time
11] 2
124. Feel different or left out because of your
asthma? QA LFcc/[)z_'(li'rc77t
How bothered have you been during the past week by:
1-
Extremely
Bothered
[1] 2

125. Shortness of breath Q.~ll..S‘/mrnics.sQ/Brmili

157

3

3

3

3

3

3

Some
of the
time

[4]

4.
Somewhat
Bothered

[41

Some
of the
time

[41

4.
Somewhat
Bothered

14]

Some
of the
time

14]

4-
Somewhat
Bothered

I41

5

5

5

6

6

6

6

6

6

None
of the
time

171

7- Not
Bothered
[71

None
of the
time

17]

7- N ot
Bothered
171

None
of the
time

[71

7- Not
Bothered
I71

In general, how often during the past week did you:

4- 7-
1- All Some None
of the of the of the
time time time

[1] 2 3 [4] S 6 [7]

126. Feel frustrated because you couldn't keep up
with others? Q4 LFrustramlCou/dn(Keep Up

127. Wake up during the night because of your
asthma? QAL li’okeUp

128. Feel uncomfortable because of your asthma?
Q4 L L’ncoinfm'talile

129. Feel out of breath because of your asthma?
QA LOutO/Breatli

130. Feel you couldn't keep up with others because
of your asthma? Q4 LC oulrlntlx’ccp Up

131. Have trouble sleeping at night because of your
asthma? Q4 L Traubl cSl ccpi n g

132. Feel frightened by an asthma attack?
Q4 1. Frightened

Think about all the activities that you did during the past week.

1- 4-
Extremely Somewhat 7- Not
Bothered Bothered Bothered

[1] 2 3 [4] 5 6 [7]
133. How much were you bothered by your
asthma during these activities?
Q 4 l- Bothered Darin gA Clll 'ities

In general, how often during the past week did you:

4- 7-
1- All Some None
of the of the of the
time time time

[1] 2 3 [4] 5 6 [7]

134. Have difﬁculty taking a deep breath?
Q4 l. Di [ii (‘Ill til'DeepBreatli

158

Section: Demographics
Demographics (Demographics)

These next few questions will help us to describe the group of students taking part in this project.

135. What is your age?Age
0 number

VALIDIF: isEmpty(Age) or answerWithinRange(Age. 10, 25)

136. What is your birthdate? (Please tell us month, day, and year in this format: 00/00/00)Date0fBirth
0 date

137. What is your race?Race

Caucasian (or White), non-hispanic [Caucasian]

African American (or Black), non-hispanic [Black]

America Indian [Amerindian]

Asian

Paciﬁc Islander [PaciﬁcIslander]

Hispanic

Other or Multi-racial [Other]
Unknown

138. Are you male or female?Gender

0 Male
0 Female

139. What grade are you in now?Sc-hoolGrade

9th [9]
10th [10]
11th[11]
12th[12]

140. There are many health conditions that are associated with our size. Please tell us...
How much do you weigh? W zight
0 number

VALID/F: isEmptylWeight) or 50 <=ﬂ0at(Weight) <= 750

159

141. How tall are you?l-lciglzrl~‘cct

-- height in feet -- [0]
3 feet [3]
4 feet [4]
5 feet [5]
6 feet [6]
7 feet [7]

142. What is the highest grade of school that your mother has completed?.llinherl? 1'lll(‘(lll()ll

Less than 8th grade [LessThan8th]
Some high school [SomeHighSchool]
High school graduate [HighSchoolGrad]
Some college [SomeCollege]

College graduate [CollegeGrad]

Don't Know [DK]

143. What is the highest grade of school that your father has COITIpiCth?/T(illlt’l‘lfrlllc'ullrm

Less than 8th grade [LessThan8th]
Some high school [SomeHighSchool]
High school graduate [HighSchoolGrad]
Some college [SomeCollege]

College graduate [CollegeGrad]

Don't Know [DK]

160

144. What health insurance do you have?HealthInsurance

Aetna

Blue Care Network [BlueCareNetwork]
Blue Cross / Blue Shield [BCBS]

Botsford Health Plan [BotsfordHealthPlan]
Cape

Care Choices [CareChoices]

Children's Choice [ChildrensChoice]
Cigna

DMC Care [DMCCare]

Great Lakes Health Plan [GreatLakesHealthPlan]
Health Alliance Plan (HAP) [HAP]

Health Plan of Michigan [HealthPlanOfMichigan]
Kids Care [KidsCare]

M-Care [MCare]

Midwest

Molina

Omnicare

Prudential

SelectCare

Total Healthcare [TotalHealthcare]
Travelers

Ultimed

Wellness

Don't Know [DK]

No insurance [None]

145. Is this through Medicaid?Hus,«llulicairl

0 Yes
0 No
0 Don't Know [DK]

146. Does this health insurance cover the cost of medications your doctor may prescribe for asthma
symptoms like wheeze, cough, chest tightness, or shortness of breath?ll chicuiimz(me/age

0 Insurance covers ALL of the cost of medications I take for asthma symptoms like wheeze, cough,
chest tightness, or shortness of breath. [AllCost]

0 Insurance covers MOST of the cost of medications I take for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath. [MostCost]

0 Insurance covers SOME of the cost of medications I take for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath. [SomeCost]

- Insurance covers NONE of the cost of medications I take for asthma symptoms like wheeze,
cough, chest tightness, or shortness of breath. [NoneCost]

0 Don't know [DK]

161

147. During the past 12 months, was there a period of time when you were not covered by health
insurance?Healt/1/ns u)‘ancrt’UapLast l 3.1/midis

0 Yes
No
0 Don't Know [DK]

Section: Goodbye
Goodbye

THAT'S IT! That's the end of the questions!
We are glad you have decided to try Puff City.

You should return to the computer for your ﬁrst Puff City asthma management session sometime between
[date] and [date].

Here's a preview of what you can expect: (bouncing building intro and music).

162

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