1. No category

Objectives:
• Identify the components of a research article
How to Review a Research Article
• Use a systematic approach to evaluate a
nursing research article
Bernice D. Mowery, PhD, PNP, RN
Pediatric Nursing Conference
What Do You Need to Review
Research Articles?
• Fears?
• Learn terminology
• Get help with statistics
• Evidence Based Practice (EBP)/Best Practice
• How do you determine if a research article is
applicable?
• Is one article enough to support practice change?
• Plan
• Learn components of a Research Study
• Evaluate the quality of how it was done
• Use a systematic format to evaluate studies
Evidence-Based Practice: Six Steps
1. Formulation of an answerable question to address a specific
patient problem or situation
2. Systematic searching for the research evidence that could
be used to answer the question
3. Appraisal of the validity, relevance and applicability of the
research evidence
4. Integration of the research evidence with other information
that might influence the management of the patient's
problems: clinical expertise, patient preferences, available
resources
5. Implementation of the evidence-based practice decision
6. Evaluation of the outcome of the decision
http://ktclearinghouse.ca/cebm/syllabi/nursing/intro
COMPONENT
Clarity of the problem & Significance for nursing
Tips for Review
• Use same approach each time
• Develop your own system
• Use a form to record your evaluation
• Write notes in margins as you read or use Track
Changes
• May need to review several times before final evaluation
• Review all articles on subject - then review again
• Rank them for relevance and quality
• Synthesize
Research Article
Evaluation Form
Bernice D. Mowery,
PhD, PNP, RN
Article
Information: …
Aims/Research ?s/Hypotheses
Conceptual/Theoretical Framework
Literature Review
Type of Study: Quantitative; Qualitative or Mixed
Method
Study Design/Methodology
•Quantitative: Experimental,
Quasi-experi, Non- experi
•Qualitative: Grounded theory,
Phenomenology, Ethnography
Ethical considerations
Operational Definitions
Study Population/Sample: Types of patients
Number of subjects/Power Analysis
Gender, Race, Age Group
Setting
Sampling Method
Interventions Studied
Intervention or Exposure
or Treatment
Outcomes
Mode of Measurement
Psychometric Characteristics
Multidimensional
Attrition /Withdrawals for adverse reactions
Findings/Results
Data Analysis/Themes
Scoring
Significance
Effect Size
Validity Threats
Construct Validity
Internal Validity
External Validity
Statistical Conclusion
Validity Threat
Methodological Strengths
Limitations/Weaknesses
Authors’ Conclusions and General Comments
Conclusions:
COMMENTS
Critique of the Research Process
Overview of the Article
• Author(s)
• Not just “yes” or “no” for each step
• Date of the research
• Evaluate quality
• Title clear?
• No such thing as “perfect” research
• Abstract helpful?
• Want the most strengths possible with limitations in areas
of least importance for this study
• What are clinical implications?
• Priority area for nursing research
• Focus of EBP (evidence based practice)
• Is the approach quantitative or qualitative?
Purpose/Problem Statement
Aims/Objectives/ Research Questions
•
Different words used to describe
– Goals of the research
– Are they logical & realistic
– May include hypotheses
•
Theoretical/Conceptual Framework/Model
– Adequately described
– Appropriate
– Controversial if this is an absolute requirement
• Clarity of the problem
• Research aims/questions/hypotheses
• Builds on previous research
• Significance for nursing
Background/Literature Review
•
Review comprehensive
•
Support for the current research questions
•
Includes most current information
•
Includes all pertinent variables
•
Establishes significance
Methods:
•
•
•
Type of study approach
– Should match questions
– Qualitative
– Quantitative
– Mixed methods
IRB approval/human rights protection
Procedures
– Operational definitions for Measures & Outcomes
– Participants
– Plan for analysis
Study Design
Quantitative vs. Qualitative
• Quantitative
• Study of phenomena that can be precisely measured and quantified
• Statistical analyses
• Quantitative
• Experimental
• Random Controlled Trial
• Quasi-experimental Design
• Qualitative
• Study of phenomena in an in-depth & holistic manner
• Participant’s perspective of the phenomena (narrative data)
• Non-experimental
•
•
•
•
• Mixed methods
• Combine Quantitative & Qualitative methods
• Triangulation: research process along with data is analyzed from
different directions – decreases bias & increases validity of results
Quantitative Design
Study Design
• Investigation of phenomena that that allows precise
measurement and quantification
• Usually involves rigorous and controlled design (Polit & Beck,
• Qualitative
• Grounded theory
2012)
• Characterized by
• Systematic collection and statistical analysis of
numerical data
• Relatively controlled conditions (Norwood, 2010)
• Gathering and analyzing empirical evidence
• Goal is generalizability (Polit & Beck, 2012)
• Phenomenology
• Ethnography
Qualitative Design
• Study of phenomena in an in-depth & holistic
manner
• Participant’s perspective of the phenomena
(narrative data)
• The “lived experience”
Descriptive
Correlational
Blinding
Intervention (independent variable)
Ethical Considerations
•
•
•
•
Human rights protection
All risks identified
Participants fully informed
Consent/Assent given
• The National Commission for Protection of Human Subjects of
Biomedical and Behavioral Research established age 7 as a
reasonable minimum age for involving children in some kind of
assent process
• Younger may be able to assent
• Funding influences
• Investigator bias
Procedures
Sample/Study Population
• Described adequately
– To allow reviewer to evaluate
– For duplication
• Operational definitions for
– Interventions/Exposure/Treatment (Independent
variable)
– Outcomes (Dependent Variable)
• Realistic
– Is it cost-effective?
– Would this ever work in practice?
•
Sample Size: Power Analysis or Saturation
•
Gender
•
Race
•
Setting
•
Age group
•
Sampling method
•
Same group as your interest
Findings/Results
Measurements
•
•
•
Multidimensional
• Different tools to measure different dimensions of
outcome
• Different tools to measure same dimension of
outcome
• Mono-measurement is a threat to validity of the
study
Psychometric Characteristics
• Reliability
• Validity
•
•
•
Statistical Tests
• Bivariate:
• t-test
• ANOVA
• Chi-Square
• Pearson’s r
• Multivariate
• MANOVA
• Multiple Regression
• Logistical Regression
Data and Analyses
• Statistical analysis planned met assumptions
• Do graphs and tables correlate with statistical report
Significance
• Statistical
• Clinical
Effect size
Qualitative:
• Themes & meaning elicited
• Saturation reached
Rigor
•
•
•
•
•
Striving for excellence in the research process
Uses discipline
Strict adherence to detail
Extremely accurate
Precision
• Control over confounding/extraneous/intervening variables that could
affect the dependent variable
• Effect size and Power
• Effect size = the magnitude of difference the intervention makes on
the outcome
• Maximize differences made by the independent variable
• Power is probability that a statistical test will detect a difference
Validity Threats
Random Controlled Trial (RCT)
Three areas required:
•
Construct Validity
•
Internal Validity
•
External Validity
•
Statistical Conclusion Validity Threat
Construct Validity
• Most often associated with measurements
• Key questions:
• What is the instrument measuring?
• Does it validly measure the abstract concept of
interest?
• Use both logical and empirical procedures to evaluate
• Use what is known to evaluate relationships in
variables
• Factor analysis – statistical method to identify clusters
of related items on a scale
Selection-Treatment Interaction
• Bias from preexisting differences
• RCT helps control for this
• If not RCT, this is most significant threat to internal
validity
• Also an issue if many elect not to receive the
treatment
1. Randomization
• Random sample
• Random assignment to control and
experimental groups
• Difficult to obtain random sample in clinical
setting so most researchers use a convenience
sample with random assignment
2. Comparison or control group
3. Controlled manipulation of the
treatment/independent variable
Internal Validity
• Did the experimental treatment(s), and not some
extraneous variable, make the difference in this
specific experimental instance?
• Common Threats:
• Selection-Treatment interaction
• History
• Maturation
• Mortality/Attrition
• Fishing/Error rate
History
• Occurrence of events simultaneously with the
intervention/independent variable
• Not sure which one is causing the effects
• Controlled by RTC – both groups (experimental &
control) are affected by history
Maturation
Mortality/Attrition
• Time causes effects rather than intervention
• Longitudinal studies may loose participants over time
• Lots of issues we study are affected by time
• Coping
• Wound healing
• One-group before – after design is most
vulnerable
• Control: RCT – both groups affected
• Those who drop out may be different from those that
continue
Fishing/Error Rate
• If you keep evaluating enough variables,
something will be significant when really it is not
• Attrition bias is same as selection bias
• Higher rates of attrition pose great validity threats
• Rates > 20% yield concerns about bias
Methodological Strengths
•
Control of extraneous variables
•
Sample large enough
• Analysis of variables without any theoretical or
other support
•
Does the experimental design control for
competing influences = confounding variables
• Outcomes report should match research
aims/questions
•
Experimental rigor
External Validity
• Degree to which you can apply findings of this study to
other settings and samples
• Consider the characteristics of the study participants
• Threats:
• Reliability of treatment implementation
• Statistical Regression
• Best control for threats is RCT design
Reliability of Treatment Implementation
• Described thoroughly enough?
• Were treatments consistent?
• Consistent person did all treatments
• Workshop training for those providing treatments
• Checks for consistency
• Were effects dependent on the person who provided
the treatment?
Statistical Conclusion Validity
•
Affected by
• Sample size & Power
• Strength of intervention (independent variable)
Conflicts for validity
Tight study for internal validity may make
the intervention not applicable to
the real world
• Strength of the outcomes (dependent variable)
Discussion, Author’s Conclusions and
General Recommendations
Conclusions
•
Did author recognize threats and limitations of study?
• Drawn from the findings
•
Recommendations for improvements to repeat study
• Logical
• Generalized to other groups
• Limitations affect generalizability
Generalizability
• Infers that findings can be generalized from the
study sample to a broader group (i.e. population)
• Important when looking for support for evidence
based practice to determine if the findings of a
study are applicable to your interest group
• For example:
• Would findings from a study evaluating an
intervention for chronic pain be applicable for
post-operative pain management?
Conclusions, Implications and
Recommendations
• Rigorous
• Practice/EBP
• Research
PRACTICE, PRACTICE, PRACTICE
Adherence in Single-Parent Households
In a Long-Term Asthma Clinical Trial
Mary Spicher, Nancy Bollers, Tamara Chinn, Anita Hall, Anne Plunkett,
Denise Rodgers, D.A. Sundström, Laura Wilson, The Childhood Asthma
Management Program (CAMP) Research Group
A
dherence is the extent to
which a patient follows a
reasonable treatment that
has been prescribed for him
or her by a qualified caregiver
(Bender, Milgrom, & Rand, 1997).
Non-adherence is of widespread concern in the medical community.
Bender et al. (1997) found that
patients’ symptoms and the need to
use the medical care system for acute
care could all be reduced by improved
adherence. Additional consequences
of non-adherence for many patients
and parents can be missed work or
school days (Bender et al., 1997).
Quality of life has been found to improve if persons are adherent to their
prescribed medications (Mannheimer
et al., 2005). The World Health
Organization defines adherence as the
Mary Spicher, MSN, RN, is a Research
Coordinator, University of New Mexico,
Albuquerque, NM.
Nancy Bollers, RN, is a Registered Nurse
(Retired), Venice, FL.
Tamara Chinn, ARNP, is a Study
Coordinator, ASTHMA, Inc., Seattle, WA.
Anita Hall, RN, is a Clinical Research Nurse
Coordinator, The Hospital for Sick Children,
Toronto, Ontario, Canada.
Anne Plunkett, MS, NP, is a Nurse
Practitioner and Research Coordinator,
Harvard Vanguard Medical Associates,
Boston, MA.
Denise Rodgers, BS, RPFT, is a Clinical
Research Coordinator, Washington University,
St. Louis, MO.
D.A. Sundström, BA, is a Pediatric Clinical
Research Manager, National Jewish Health,
Denver, CO.
Laura Wilson, ScM, is a Biostatistician,
Bloomberg School of Public Health, Johns
Hopkins University, Baltimore, MD.
The Childhood Asthma Management
Program (CAMP) Research Group. Please
see credit roster at the end of this article.
Adherence of participants in a long-term clinical trial is necessary to assure validity of findings. This article examines adherence differences between single-parent
and two-parent families in the Childhood Asthma Management Program (CAMP).
Adherence was defined as the percentage of completed daily diary cards and
scheduled study visits during the course of the trial. Logistic regression and ordinal
logistic regression analyses were used. Children from single-parent families had a
lower percentage of completed diary cards (72% vs. 84%) than two-parent families.
Single-parent families were also more likely to reschedule visits (62% vs. 45%) and
miss more clinic visits (23% vs. 17%) than two-parent families. Suggestions are
given for study coordinators to assist participants in completing a long-term clinical
trial. Many suggestions may be adapted for nurses in inpatient or outpatient settings for assisting parents of patients with chronic diseases.
extent to which a person’s behavior
(in terms of taking medications, following diets, or executing lifestyle
changes) coincides with the instructions given by health care providers
(Sabeté et al., 2003). In addition, lack
of adherence to clinical research protocols, which includes the recording
of outcomes, attending scheduled visits for measurements, and taking of
medication, can threaten the validity
of the findings of a study. Determining factors that have a significant
impact on adherence in a clinical trial
can improve the selection process as
well as identify patients with chronic
diseases that might benefit from
added attention and instruction.
The purpose of this study was to
determine if adherence in a long-term
clinical trial of asthma therapy is
decreased in single-parent families.
Single-parent households make up
25% of households in the United
States. Specifically, the researchers
wanted to test the hypothesis that
single-parent families would be less
adherent than two-parent families
during a long-term asthma clinical
trial. The researchers analyzed data
from children and families enrolled in
the Childhood Asthma Management
Program (CAMP), a 4- to 6-year clinical trial comparing two anti-inflammatory medications with placebo in
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
children with persistent asthma. All
children received inhaled albuterol as
needed for symptoms (CAMP
Research Group, 1999).
Methods
The design and methods of the
CAMP trial as well as the main outcomes have been detailed elsewhere
(CAMP Research Group, 1999, 2000).
Pertinent to this ancillary study were
the following: 1) 1041 children 5 to
12 years of age were enrolled across
eight clinical centers, and 2) clinical
research coordinators were initially
trained and certified centrally to
establish standardization across all
eight centers for visitation schedule
and the measuring and recording of
outcomes that were then submitted
to a central data coordinating center
(CAMP Research Group, 1999). In
addition, a centralized asthma educational group was formed to develop
and disseminate ongoing standardized asthma education across the centers to improve and maintain adherence to the study protocol (CAMP
Research Group, 1998). Approval for
all study procedures was obtained
from the Institutional Review Board
at each institution. Parents and children signed consent and assent forms
respectively.
207
Adherence in Single-Parent Households in a Long-Term Asthma Clinical Trial
Table 1.
Characteristics of the CAMP Participants at Baseline
Age – Year (Mean ± SD)
Range
Single-Parent
Family
(n = 177)
9.0 ± 2.1
Two-Parent
Family
(n = 854)
8.9 ± 2.1
Total
(N = 1031)
8.9 ± 2.1
5 to 13
5 to 13
5 to 13
Race or Ethnic Group – %
< 0.0001
Minority
55.9%
26.4%
31.4%
Non-minority
44.1%
73.7%
68.6%
Sex – %
0.26
Female
44.1%
39.5%
40.3%
Male
55.9%
60.5%
59.7%
Mild
49.2%
47.5%
47.8%
Moderate
50.9%
52.5%
52.2%
Less than $15,000
21.1 %
3.8%
6.8%
$15,000 to $29,999
33.3%
14.2%
17.5%
$30,000 to $49,999
36.8%
32.7%
33.4%
8.8%
49.3%
42.3%
Severity of Asthma – %
0.70
Annual Income – %
< 0.0001
$50,000 or more
Annual Income Among Caucasians – %
< 0.0001
Less than $15,000
21.1%
3.3%
5.3%
$15,000 to $29,999
35.5%
13.0%
15.5%
$30,000 to $49,999
34.2%
30.5%
30.9%
9.2%
53.1 %
48.2%
$50,000 or more
Annual Income Among Minorities – %
< 0.0001
Less than $15,000
21.1%
5.2%
10.1%
$15,000 to $29,999
31.6%
17.4%
21.8%
$30,000 to $49,999
39.0%
39.0%
39.0%
8.4%
38.5%
29.2%
High school education or less
19.8%
10.0%
11.7%
Some college
47.5%
35.1%
37.3%
Completed college
32.8%
54.9%
51.1%
$50,000 or more
†
Education Level – %
< 0.0001
Education Level Among Caucasians – %†
< 0.0001
High school education or less
21.8%
8.8%
10.2%
Some college
51.3%
33.3%
35.3%
Completed college
26.9%
58.0%
54.5%
Education Level Among Minorities – %†
0.27
High school education or less
18.2%
13.3%
14.8%
Some college
44.4%
40.4%
41.7%
Completed college
37.4%
46.2%
43.5%
35.9 ± 11.4
32.2 ± 10.2
32.8 ± 10.5
19 to 73
19 to 73
19 to 73
‡
Impact on Family Scale (IFS) Score
Mean ± standard deviation
Range
p -Value*
0.68
< 0.0001
Source: United States Census Bureau, 2003.
*Unadjusted p-value for homogeneity among groups.
†
If two-parent household, parent with highest education level was used.
‡
Impact on Family Scale, which is completed by the parent, is a measure of family quality of life related to the child’s illness. The
total score ranges from 19 to 76, where higher scores indicate a greater impact on the families.
208
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
Data were obtained from forms
completed by the participants, their
parents, and from study coordinators
involved in the study. Income and
educational data were obtained by
self-report from the parents at the
start of the trial. The Impact on
Family Scale (IFS), a measure of family quality of life related to the child’s
illness, was administered to a parent
just prior to randomization and completed annually. Most measurements
obtained in the study were of the
child, but parents also had a role in
the study by completing forms, providing insight about the child, and
taking care of logistics, such as assisting with diary card completion, mailing, and transportation to clinic visits.
Participants attended three clinic
visits per year to monitor their asthma, obtain lung function measurements, and complete interim reviews.
They were instructed to contact their
center study coordinator between
clinic visits if there were any difficulties with their asthma. Participants
and parents helping younger children
were also asked to complete daily
diary cards that recorded daily morning and evening peak flows, awakening at night by asthma symptoms, use
of study and rescue medications,
absence from school due to asthma,
contacting the physician for asthma
symptoms, and severity of symptoms.
Participants and their parents were
given stamped return envelopes to
use for mailing diaries to the clinics
between visits.
Coordinators provided information regarding family status (singleparent or two-parent) at the beginning of the study and at the conclusion of CAMP. The study coordinators
characterized the frequency with
which patients had rescheduled their
visits, categorizing each patient as
someone who frequently or chronically rescheduled visits (5 to 7 times),
occasionally rescheduled visits (3 to 5
times), or rarely/never rescheduled
visits (0 to 2 times). If no visits were
missed, participants should have
completed a minimum of 14 and a
maximum of 18 clinic visits depending on date of randomization into the
study. The coordinators would typically schedule a visit early in the allotted visit time window to allow as
much time as possible for the visit to
be completed in case of rescheduling.
A visit was considered missed if none
of the study data for that visit were
completed. Adherence was defined as
percentage of daily diary cards filled
out and the number of missed or
rescheduled clinic visits in the CAMP
study. Diary card non-adherence was
defined as less than 75% of diary days
not completed. If at least one item for
the day was filled out, the diary was
considered completed for that day.
Statistical Methods
Logistic regression and ordinal
logistic regression analyses were used
to evaluate the association between
family status and the three measures
of non-adherence: 1) percent of diary
cards with any data, 2) missed clinic
visits (at least 1 missed versus none),
and 3) a tendency to reschedule clinic visits – frequently, occasionally, or
rarely/never. These models were used
to calculate the adjusted relative odds
(RO) of non-adherence for single- versus two-parent families. All models
were adjusted for age at randomization, gender, race, income at randomization, asthma severity at randomization, IFS score at baseline, treatment
group, and clinic.
Due to the small number of children missing more than one visit,
missed clinic visits were dichotomized into zero missed visits versus
one or more missed visits. All analyses
were performed with SAS software
version 8 (SAS Institute, Inc., Cary,
NC).
Results
CAMP study participants ranged in
age from 5 to 12 years at the beginning of the study and participated in
the study an average of 4.3 years.
There were 1041 participants randomized into the study. The study
coordinators were unable to characterize the family status for 10 participants, so data from 1031 participants
were analyzed. The mean ± standard
deviation age of the participants in
the study was 8.9 years ± 2.1, with
59.7% males, 68.6% Caucasian, and
31.4% minorities. The breakdown of
minorities is 13% African American,
9.5% Hispanic, and 8.9% other. The
other category of minorities consisted
of Asian, Native American, Native
Alaskan, and Native Hawaiian or
other Pacific Islander populations.
The proportions of participants from
single-parent families were more likely to be minority race/ethnicity than
participants from two-parent families
(p < 0.0001) (see Table 1). Asthma severity was evenly distributed between
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
mild and moderate within the singleand two-parent families. Annual
income was categorized as less than
$15,000, $15,000 to $29,999, $30,000
to $49,999, and $50,000 or more. As
expected by national data, incomes of
single-parent families were lower than
those of two-parent families (see Table
1) (U.S. Census Bureau, 2003).
On average, 82.1% of diary cards
distributed during the course of the
trial were completed (see Table 2), and
76.9% of participants were categorized as being adherent with diary
card completion. Eighty–two percent
of participants did not miss any clinic
visits during the trial. Fifty-two percent never or rarely rescheduled, so
slightly less than half sometimes or
frequently rescheduled visits (see
Table 2).
Children from single-parent families had a lower diary card completion rate (72.4% vs. 84.1%, p <
0.0001) and had a greater number of
missed visits (0.9 vs. 0.6, p = 0.03). In
addition to missed visits, single-parent families were more likely to
reschedule visits: 31.6% were categorized as frequently rescheduling visits
vs. 20.1% for two-parent families (p =
0.0001) (see Table 2).
Over time, children from both single- and two-parent families became
less adherent with completing diary
cards, but children from single-parent
families had a greater decrease than
children from two-parent families (see
Table 3). When comparing diary card
completion in the first six months of
the study to the last six months of
study participation, diary card completion rate dropped by 25% among
single-parent families vs. 13% among
two-parent families. During the last
six months of study participation,
children from single-parent families
completed only 66.4% of diary cards,
while children from two-parent families completed 82.4% (p < 0.0001).
Ninety-one percent of children from
single-parent families had no missed
visits in the first six months vs. 90%
in the last six months of participation, compared to 95% in the first six
months and 91% in the last six
months for two-parent families.
Although adherence decreased
slightly over the duration of the trial,
children from both single- and twoparent families showed a decrease in
IFS score, indicating the impact of the
children’s asthma was lessening over
time (Bender et al., 2000). This was
reflected in asthma severity assessed
209
Adherence in Single-Parent Households in a Long-Term Asthma Clinical Trial
Table 2.
Adherence over Course of Trial
Single-Parent
Family
(n = 177)
Two-Parent
Family
(n = 854)
Total
(N = 1031)
Percent of days with diary cards completed†,
mean ± SD (range)
72.4 ± 27.3
(1.2 to 99.0)
84.1 ± 22.6
(0.2-99.9)
82.1 ± 23.9
(0.2 to 99.9)
Number of missed visits, mean ± SD (range)
0.9 ± 2.3
(0 to 14)
0.6 ± 2.1
(0 to 14)
0.7 ± 2.1
(0 to 14)
0.03
76.8%
83.5%
82.4%
0.03
Frequently rescheduled
31.6%
20.1%
22.0%
Sometimes rescheduled
29.9%
24.9%
25.7%
Rarely/never rescheduled
38.4%
55.1%
52.3%
Adherence Measure
Patients with no missed visits – %
Tendency to reschedule visits – %
p -Value*
< 0.0001
0.0001
*Unadjusted p-value for homogeneity among groups.
†
For diary day to be counted as complete, at least one item on the diary card must have been completed each day.
Table 3.
Change in CAMP Participants Over Study Follow-Up Time
Single-Parent
Family
(n = 177)
Two-Parent
Family
(n = 854)
Change in asthma severity**
p -Value*
0.86
Asthma less severe or in remission, compared to baseline
37.3%
39.0%
Asthma more severe, compared to baseline
11.1%
9.9%
No change in asthma severity
51.6%
51.2%
Change from baseline in IFS score – Mean ± SD***
-5.6 ± 11.7
-4.1 ± 10.6
0.10
Percent of days with diary cards completed in the first 6 months of CAMP –
Mean ± SD
88.7 ± 19.0
94.2 ± 12.7
< 0.0001
Percent of days with diary cards completed in the last 6 months of CAMP –
Mean ± SD
66.4 ± 37.3
82.4 ± 27.4
< 0.0001
Percent of patients with no missed visits in the first 6 months of CAMP
91.0%
94.9%
0.04
Percent of patients with no missed visits in the last 6 months of CAMP
89.8%
90.5%
0.78
*Unadjusted p-value for homogeneity among groups.
**N = 923 because of missing data or because asthma severity may have been categorized as “other.”
***Impact on Family Scale, which is completed by the parent, is a measure of family quality of life related to the child’s illness.
The total score ranges from 19 to 76, where higher scores indicate a greater impact on the family.
during the first six months and last six
months of the trial (see Table 3). The
results were comparable between singleand two-parent families (p = 0.86).
There was no change in asthma severity
in 51% of the participants overall.
Asthma was less severe or in remission
in 37% of single-parent families and
39% in two-parent families. Participants
whose asthma became more severe
were 11% in single-parent families and
almost 10% in two-parent families.
Results from a logistic regression
analysis showed that family status was
found to be associated with nonadherence, adjusted for age, gender,
210
race, income, asthma severity, IFS
score, treatment group, and clinic (see
Table 4). Children from single-parent
families were more likely to be nonadherent with diary card completion.
The adjusted relative odds for diary
card non-adherence among children
from single-parent families versus
those from two-parent families were
1.85 (95% confidence interval, 1.24 to
2.76, p = 0.003). There was no difference in the adjusted relative odds of
having a missed visit (p = 0.34), but
single-parent families were more likely
to reschedule clinic visits than twoparent families. The adjusted relative
odds of frequently rescheduling versus
occasionally or rarely/never rescheduling were 1.57 for single-parent families compared to two-parent families
(95% confidence interval, 1.10 to
2.23, p = 0.01).
Discussion
Adherence in the CAMP trial was
very high regardless of family status.
Overall, there was 82% compliance in
diary cards, and 82% of participants
did not miss a visit during the fiveyear trial. Fifty-two percent of participants infrequently rescheduled a visit.
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
Table 4.
Association of Parental Status with Noncompliance of Child*
Odds Ratio
95% CI
p-Value
Diary Card Non-Compliance**
1.85
1.24 to 2.76
0.003
Missed visits***
1.25
0.79 to 1.99
0.340
Rescheduled visits****
1.57
1.10 to 2.23
0.010
*Odds ratios, 95% confidence intervals (CIs), and p-values from logistic regression
model of noncompliance measures (diary card noncompliance, missed visits, and
rescheduled visits on family status at baseline (single parent family: two parent family). All models were adjusted for age at randomization, gender, race, income at randomization, asthma severity at randomization, IFS score at randomization, treatment
group, and clinic.
**Diary card noncompliance is defined as less than 75% of diary cards not completed.
***Missed visits were categorized as missing one or more visits versus missing zero
visits due to the small number of children missing more than one visit.
****Families were categorized as frequently rescheduled visits, occasionally rescheduled, or never/seldom rescheduled. Ordinal logistic regression was used to model
the tendency of the family to reschedule clinic visits on family status at baseline.
The percentage of non-adherence
among single-parent families was
much less than originally hypothesized. The hypothesis formed prior to
the data analysis was that there would
be a much greater percentage of nonadherence among single-parent families. The U.S. Census Bureau (2003)
stated that single-parent families
account for 23% of the nation’s families. Because single-parent families are
only slightly less adherent than twoparent families as shown by this clinical trial, these families should continue to be included as participants in
research studies because they represent approximately one-fourth of
families in society.
This diminished adherence of single-parent families could be due to the
difficulty of single parents with transportation issues or work situations.
Several single parents reported the following reasons they had difficulty
attending the scheduled clinic visits:
1) inability to take time off work, 2)
babysitting problems for the other
children in the home, and 3) time
constraints. In general, single-parent
families have lower incomes than twoparent families. In the CAMP trial,
54% of single-parent families had an
annual income of less than $30,000,
and only 9% had an income of
$50,000 or more. Single-parent families had less post-secondary education,
and 33% versus 55% two-parent families completed college (as obtained by
self-report of parents at enrollment
into the study). These factors would
allow for fewer advantages and less
time available for the child.
During each study visit, participants and families received standardized education regarding their disease,
treatment for their disease, and any
difficulties participants might have
living with their disease. Some participants incorporated their asthma education into science fair projects for
school. Education improves the ability to manage the disease and can prevent emergency room visits and hospitalizations (Lara et al., 2002;
Wallace, Scott, Klinnert, & Anderson,
2004). Participants often have difficulty understanding the reasons for
asthma treatment (Bender, 2002);
therefore, educating the participant
regarding his or her disease leads to
self-management of the disease
(Conboy-Ellis, 2006). The CAMP standardized ongoing education program
was likely a contributor to overall
good adherence in the study (Bender
et al., 2003).
A major determinant of adherence
is the trust developed between the
participant and the health professional (Bender et al., 2003; DiMatteo,
2004). A participant is more willing to
complete treatment if he or she
believes there is a commitment from
the health professional (Jonsson,
Lindberg, Oscarson, & Ohrn, 2006),
feels listened to by the clinician
(Bender et al., 2003; Bender, 2005),
and receives consistent reinforcement
with positive feedback (Strunk et al.,
2002). Health care workers must make
special efforts to be supportive of their
clients (Coleman, Hall-Barrow, Coon,
& Stewart, 2003).
Limitations to this study include
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
the lack of randomization of singleparent and two-parent families.
Race/ethnicity, income, education,
and Impact on Family scores were different between the family groups.
These factors could have contributed
to the differences in adherence observed in single-parent vs. two-parent
families. Thus, factors that demonstrated statistically significant differences were controlled for in the regression analysis. Further, the study
was not designed to determine
whether the level of adherence affected patient outcomes; researchers were
primarily interested in whether single-parent families should be recruited into clinical trials.
Implications of Nursing
Practice
During the CAMP trial, attempts
were made to reduce difficulties families might have in continuing in a
long-term trial. These measures were
for all families but appeared to be
especially valuable for the single-parent families. Centers reimbursed participants for transportation, sent a
taxicab to pick up the participants, or
scheduled appointments during
evenings or on weekends to accommodate working parents. If a parent
was unable to miss work, grandparents or other family members would
sometimes accompany the child to
the visit. The parent was reachable by
telephone to answer any questions
the family member was unable to
answer. As participants became older,
they would come to the visit alone
and answer questions regarding their
asthma. The coordinators were also
able to send forms home with the
child to be completed by the parent
and returned in a stamped selfaddressed envelope.
All of the centers had incentives in
addition to a reimbursement amount
given at each visit. Activities were
planned as group events (for instance,
attending a sporting event, plays,
movies, or amusement parks). Some
of these outings were beyond the
financial reach of some families, but
their children were able to enjoy the
event because the cost was paid by
the trial. The centers had “CAMP
stores” where participants would
receive points for attending clinic visits and turning in diary cards.
Participants could spend their points
at the store. A variety of items were
geared to the ages and interests of the
211
Adherence in Single-Parent Households in a Long-Term Asthma Clinical Trial
children. Participants would be asked
periodically what type of items they
would like to see in the store. As the
study participants matured, the
“CAMP store” added gift certificates
to stores along with the items available for exchange.
The coordinators at the various
centers made an effort to make the
CAMP visit a positive experience for
participants and their families. They
developed a trusting relationship with
these families while monitoring participants’ asthma for the length of the
trial. This encouraged continued participation from all families.
Many methods used in the clinical
trial could be adapted for use in nursing practice. Education was a vital
component in the study as it must be
for all patients whether seen in hospitals, outpatient clinics, or in research
studies. Nursing staff must be supportive of patients, develop a sense of trust,
and be willing to answer their questions. Another approach to ensure
patient adherence is to follow up with
those who have missed appointments
and/or rescheduled appointments, and
accommodate their needs when possible. These suggestions add minutes to
an overloaded schedule but can have
enormous impact on the quality of the
patient care.
CAMP Credit Roster (April 2009)
Source of Funding
The Childhood Asthma Management Program Trial and CAMP
Continuation Study were supported by contracts NO1-HR16044, 16045, 16046, 16047, 16048, 16049, 16050, 16051,
and 16052 with the National Heart, Lung, and Blood Institute
and General Clinical Research Center grants M01RR00051,
M01RR0099718-24, M01RR02719-14, and RR00036 from
the National Center for Research Resources.
Members of the CAMP Research Group Clinical Centers
ASTHMA, Inc, Seattle, WA: Paul Williams, MD (Principal
Investigator); Mary V. Lasley, MD (Co-Director); Tamara Chinn,
MSN, ARNP (Coordinator). Michele Hinatsu, MSN, ARNP;
Clifton T. Furukawa, MD; Leonard C. Altman, MD; Frank S.
Virant, MD; Michael S. Kennedy, MD; Jonathan W. Becker, MD;
Stephen Tilles, MD; Miranda MacLaren. C. Warren Bierman,
MD (1992-1997); Dan Crawford, RN (1996-2002); Thomas
DuHamel (1991-2004); Heather Eliassen, BA (1996-1999);
Babi Hammond (1996-1999); Dominick A. Minotti, MD (19922003); Chris Reagan (1992-2003); Gail Shapiro (1991-2006,
Principal Investigator); Marian Sharpe, RN (1992-1994);
Ashley Tatum, MD (2004-2007); Grace White (1991-2007).
Timothy G. Wighton, PhD (1994-1998).
Brigham & Women’s Hospital, Boston, MA: Anne Fuhlbrigge,
MD (Principal Investigator); Anne Plunkett, NP, MS
(Coordinator). Nancy Madden, RN, BSN; Mark Boehnert, MD;
Christine Darcy; Anita Feins, MD; Natalia Kandror, MD; Kelly
MacAulay, MD; Scott Weiss MD. Walter Torda, MD (CoInvestigator Director, 1993-2003); Martha Tata, RN (19932002); Sally Babigian, RN (1997-1999); Peter Barrant, MD
(2004-2007); Linda Benson (1998-2004); Jose Caicedo (19981999); Tatum Calder (1998-2001); Anthony DeFilippo (19942000); Cindy Dorsainvil (1998-2001); Julie Erickson (19981999); Phoebe Fulton (1997); Mary Grace, RN (1994-1996);
Jennifer Gilbert (1997-1998); Dirk Greineder, MD (1993-2000);
Stephanie Haynes (1993-1998); Margaret Higham, MD (19961998); Deborah Jakubowski (1999); Susan Kelleher (19931997); Jay Koslof, PhD (1993-1995); Dana Mandel (19961998); Patricia Martin (2001-2003); Agnes Martinez (19941997); Jean McAuliffe (1994-1995); Erika Nakamoto (20022004); Paola Pacella (1993-1998); Paula Parks (1993-1995);
Johanna Sagarin (1998-1999); Kay Seligsohn, PhD (19952004); Susan Swords (2003-2005); Meghan Syring (19982001); June Traylor, MSN, RN (1996-1998); Melissa Van Horn,
PhD (1996-1999); Carolyn Wells, RN (1993-1995); Ann
Whitman, RN (1994-1996).
The Hospital for Sick Children, Toronto, Ontario, Canada:
Hartmut Grasemann, MD (Principal Investigator); Melody Miki,
RN, BSN (Coordinator); Melinda Solomon, MD; Padmaja
Subbarao, MD. Ian MacLusky, MD, FRCP (Director 19992007); Joe Reisman, MD, FRCP(C), MBA (Director, 19961999); Henry Levison, MD, FRCP(C) (Director, 1992-1996);
Anita Hall, RN (Coordinator, 1993-2007). Yola Benedet (19941999); Susan Carpenter, RN (1998-2001); Jennifer Chay
(2004); Michelle Collinson, RN (1994-1998); Jane FinlaysonKulchin, RN (1994-1998); Kenneth Gore, MA (1993-1999);
Nina Hipolito, RN (2003-2004); Noreen Holmes, RRT (19981999); Erica Hoorntje, RN (2002-2003); Sharon Klassen,
MA(1999-2000); Joseé Quenneville, MSc (1993-1995); Renée
Sananes, PhD (1993-2004); Christine Wasson, PhD (1999);
Margaret Wilson, RN (2001-2002).
Johns Hopkins Asthma & Allergy Center, Baltimore, MD: N.
Franklin Adkinson, Jr, MD (Director); Deborah Bull, LPN
(Coordinator); Stephanie Philips, RN. Peyton Eggleston, MD
(Co-Director, 1991-2004); Karen Huss, DNSc (Co-Investigator,
1991-2004); Leslie Plotnick, MD (Co-Investigator, 1991-1999);
Margaret Pulsifer, PhD (Co-Investigator, 1993-2004); Cynthia
Rand, PhD (Co-Investigator, 1991-2004).Elizabeth Aylward,
PhD (1991-2004), Nancy Bollers, RN (Coordinator, 19932004); Kathy Pessaro (2004-2007); Barbara Wheeler, RN,
BSN (Coordinator, 1991-1999).
National Jewish Health, Denver, CO: Stanley Szefler, MD
(Director); Harold S. Nelson, MD (Co-Director); Bruce Bender,
PhD (Co-Investigator); Ronina Covar, MD (Co-Investigator);
Andrew Liu, MD (Co-Investigator); Joseph Spahn, MD (CoInvestigator); D Sundström (Coordinator); Melanie Phillips;
Michael P. White; Melanie Gleason, PA-C; Marzena Krawiec,
MD; Gary Larsen, MD; Gayle Spears, PA-C. Kristin Brelsford
(1997-1999); Jessyca Bridges (1995-1997); Jody Ciacco
(1993-1996); Michael Eltz (1994-1995); Jeryl Feeley, MA
(Coordinator, 1992-1995); Michael Flynn (1995-1996); Tara
Junk-Blanchard (1997-2000); Joseph Hassell (1992-1998);
Marcia Hefner (1992-1994); Caroline Hendrickson, RN (19951998; Coordinator, 1995-1997); Daniel Hettleman, MA (19951996); Charles G. Irvin, PhD (1992-1998); Alan Kamada,
PharmD (1994-1997); Sai Nimmagadda, MD (1993-1996);
Kendra Sandoval (1995-1997); Jessica Sheridan (1994-1995);
Trella Washington (1993-1997); Eric Willcutt, MA (1996-1997).
We also thank the pediatric allergy/immunology and pulmonary fellows for their participation (Ivan Cardona, MD;
Kirstin Carel, MD; Jayna Doshi, MD; Rich Hendershot, MD;
Jeffrey Jacobs, MD; Neal Jain, MD; June-ku Brian Kang, MD;
Tracy Kruzick, MD; Harvey Leo, MD; Beth Macomber, MD;
Jonathan Malka, MD; Chris Mjaanes, MD; John Prpich, MD;
Lora Stewart, MD; Ben Song, MD; Grace Tamesis, MD).
continued on next page
212
PEDIATRIC NURSING/July-August 2012/Vol. 38/No. 4
CAMP Credit Roster (April 2009) (continued)
University of California, San Diego and Kaiser Permanente
Southern California Region, San Diego, CA: Robert S. Zeiger,
MD, PhD (Director); Noah Friedman, MD (Co-Investigator);
Michael H. Mellon, MD (Co-Investigator); Michael Schatz, MD
(Co-Investigator); Kathleen Harden, RN (Coordinator). Terrie
Long, RN; Travis Macaraeg; Elsa Rodriguez; Eva Rodriguez,
RRT. Sandra Christensen, MD (2004-2007); James G. Easton,
MD (Co-Director, 1993-1994); M. Feinberg (1997-1998); Linda
L. Galbreath (1991-2002); Jennifer Gulczynski (1998-1999);
Ellen Hansen (1995-1997); Al Jalowayski, PhD (CoInvestigator, 1991-2005); Elaine Jenson (2004-2007); Alan
Lincoln, PhD (Co-Investigator, 1991-2003); Jennie Kaufman
(1994); Shirley King, MSW (1992-1999); Brian Lopez (19971998); Michaela Magiari-Ene, MA (1994-1998); Kathleen
Mostafa, RN (1994-1995); Avraham Moscona (1994-1996);
Catherine A. Nelle, RN (1991-2005); Jennifer Powers (20012003); Karen Sandoval (1995-1996); Nevin W. Wilson, MD
(Co-Director, 1991-1993).
University of New Mexico, Albuquerque, NM: H. William Kelly,
PharmD (Director); Aaron Jacobs (Co-Investigator);
Hengameh H. Raissy, PharmD, PhC (Co-Investigator); Mary
Spicher, RN (Coordinator). Christina Batson. Robert Annett,
PhD (Co-Investigator, 1993-2004); Teresa Archibeque (19941999); Naim Bashir, MD (Co-Investigator, 1998-2005); H.
Selda Bereket (1995-1998); Marisa Braun (1996-1999); Carrie
Bush (1995-1999); Shannon C. Bush (2002-2007); Michael
Clayton, MD (Co-Investigator, 1999-2001); Angel ColonSemidey, MD (Co-Investigator, 1997-2000); Sara Devault
(1993-1997); Anna Esparham (2004-2007); Roni Grad, MD
(Co-Investigator, 1993-1995); David Hunt, RRT (1995-2004);
Jeanne Larsson, RN (1995-1996); Katie McCallum (2009);
Sandra McClelland, RN (Coordinator, 1993-1995); Bennie
McWilliams, MD (Co-Investigator, Director, 1992-1998); Elisha
Montoya (1997-2000); Margaret Moreshead (1996-1999);
Shirley Murphy, MD (Co-Investigator, 1992-1994); Barbara
Ortega, RRT (1993-1999); David Weers (1997-1998); Jose
Zayas (1995-1996).
Washington University, St. Louis, MO: Robert C. Strunk, MD
(Director); Leonard Bacharier, MD (Co-Investigator); Gordon R.
Bloomberg, MD (Co-Investigator); Denise Rodgers, RPFT
(Coordinator). Ellen Albers (1999-2003); James M. Corry, MD
(Co-Investigator, 1995-2004); Karen DeMuth (2006-2007); Lila
Kertz, MSN, RN, CPNP (2005-2007); Valerie Morgan, RRT
(2004-2007); Cynthia Moseid (2007); Tina Oliver-Welker, CRTT
(1993-2007); Deborah K. White, RPFT, RRT (1993-2007).
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Single-Parent Households
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Research Article Review Form
Bernice D. Mowery, PhD, PNP, RN
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