Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
49
JAMIA
Original Investigations
Research Paper
■
Impact of a Computerassisted Education Program
on Factors Related to Asthma
Self-management Behavior
ROSS SHEGOG, PHD, L. KAY BARTHOLOMEW, EDD, MPH, GUY S. PARCEL, PHD,
MARIANNA M. SOCKRIDER, MD, DRPH, LOUISE MÂSSE, PHD,
STUART L. ABRAMSON, MD, PHD
A b s t r a c t Objective: To evaluate Watch, Discover, Think and Act (WDTA), a theory-based
application of CD-ROM educational technology for pediatric asthma self-management education.
Design: A prospective pretest posttest randomized intervention trial was used to assess the
motivational appeal of the computer-assisted instructional program and evaluate the impact of the
program in eliciting change in knowledge, self-efficacy, and attributions of children with asthma.
Subjects were recruited from large urban asthma clinics, community clinics, and schools. Seventysix children 9 to 13 years old were recruited for the evaluation.
Results: Repeated-measures analysis of covariance showed that knowledge scores increased
significantly for both groups, but no between-group differences were found (P = 0.55); children
using the program scored significantly higher (P < 0.01) on questions about steps of self-regulation,
prevention strategies, and treatment strategies. These children also demonstrated greater selfefficacy (P < 0.05) and more efficacy building attribution classification of asthma self-management
behaviors (P < 0.05) than those children who did not use the program.
Conclusion: The WDTA is an intrinsically motivating educational program that has the ability to
effect determinants of asthma self-management behavior in 9- to 13-year-old children with asthma.
This, coupled with its reported effectiveness in enhancing patient outcomes in clinical settings,
indicates that this program has application in pediatric asthma education.
■
J Am Med Inform Assoc. 2001;8:49–61.
Affiliations of the authors: Baylor College of Medicine (RS, MMS,
SLA) and University of Texas-Houston Health Science Center (LKB,
GSP, LM), Houston, Texas.
This work was supported in part by National Institutes of Health contract N01 H039220 from the National Heart, Lung, and Blood Institute
and by the Texas Children’s Hospital, Children’s Asthma Center.
Correspondence and reprints: Ross Shegog, PhD, Allergy and
Immunology, Abercrombie Suite 380, Texas Children’s Hospital,
6621 Fannin Street, MC 1-3291, Houston, TX 77030-2399; e-mail:
<[email protected]>.
Received for publication: 12/6/99; accepted for publication:
8/30/00.
50
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
Background
Computer-based Patient Education
This paper describes an evaluation of the impact of
Watch, Discover, Think and Act (WDTA), a computerbased educational program designed to teach asthma
self-management skills to urban, minority children.1–3 The impact evaluation assesses the program’s immediate effect on knowledge, self-efficacy,
and attributions, which are variables related to the
target behavior of self-management. It also examines
the motivational aspects of the program on children
who use it.
Computers have diverse uses in health promotion
and disease prevention—for example, as tools for
education on AIDS and responsible sexuality and as
adjuncts to medical therapy for alcohol rehabilitation
and rheumatoid arthritis.23–26 The use of virtual fantasy worlds, such as the Starbright Pediatric Network
for pediatric inpatients, has been shown to reduce
dependence on medications and to enhance pain
management.27 The Health Touch database system
has been shown to facilitate physician–patient interaction in primary care practice.28 Furthermore,
empirical research has identified the value of using
computers to provide behavior-change messages tailored to client belief characteristics, such as stage of
change and health beliefs, and to demographic characteristics, such as gender and ethnicity.29
Asthma Self-management
Asthma is among the most common chronic diseases
in the United States, and its medical and social consequences are more severe in inner-city populations.4
Asthma is characterized by chronic inflammation of
the airways that leads to episodes of bronchospasm
and excess mucus production. It has a high prevalence (about 5 percent of children under 18 years old)
and contributes significantly to school absenteeism.5–7 Asthma morbidity and mortality rates have
increased substantially among children since 1980,
and the asthma death rate among children 5 to 14
years old rose from 1.7 to 3.2 per million between
1980 and 1993.8 Asthma morbidity, mortality, and
hospitalization rates have been disproportionately
high among the poor and medically underserved.
African American and Hispanic children in the inner
cities have been reported to be more likely to have
asthma than white children. The annual prevalence
of asthma among children living in inner cities is 1.5
to 2 times higher than that of the U.S. population as a
whole.9–12
Asthma requires constant self-management by the
patient to maintain control of symptoms, prevent
exacerbations, attain normal lung function, and maintain normal activity levels. Self-management refers to
the behaviors that people with asthma and their family members perform to lessen the impact of this
chronic illness (Table 1). Self-management includes
adherence to medical regimens as well as the complex
cognitive-behavioral tasks of self-monitoring, decision making, and communicating about both symptoms and treatment regimens.13–15 Determinants of
asthma self-management behavior include a person’s
behavioral capability for management behaviors16–18
and degree of self-efficacy in performing those behaviors.13,17–19 Attribution has also been implicated in
children’s self-management behaviors and in control
of asthma and other diseases.20–22
Several computer-based applications have been developed to assist in asthma management and education.
For adult asthma patients, computer-assisted instruc-
Table 1
■
Asthma Self-management
Monitor:
■
Monitor symptoms of asthma “directly” and compare with
personal standard. Use object measures (e.g, peak flow meter)
to monitor and compare symptoms with personal standard.
■
Monitor for personal environmental triggers
■
Monitor asthma self-management efforts and compare with
personal standard
Identify problems:
■
Using monitoring (as described above), identify when a problem exists.
Implement solutions:
■
Keep regular appointments with health care providers.
■
Refer to asthma action plan.
■
Maintain medication for chronic condition as prescribed.
■
Maintain “normal” exercise levels.
■
On the basis of symptoms or the environment, make medication adjustments, including administration of rescue medication, as prescribed.
■
Avoid or remove asthma triggers.
■
Call health care professional in an acute situation.
■
Communicate with family members and with health care
providers.
Evaluate:
■
Evaluate success of actions and return to monitoring.
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
tion (CAI) has been used to help them monitor and
avoid house dust-mite allergen.30 Several CAI programs have been developed for children with asthma.
These include Clubhouse Asthma,31 Bronkie the
Bronchiasaurus,32 Wee Willie Wheezie,33 Air
Academy: The Quest for Airtopia,34 and Asthma
Command.35 Bronkie the Bronchiasaurus has been
shown to positively affect knowledge, self-efficacy,
and communication about asthma in children who use
it.36 Airtopia has been shown to positively affect asthma knowledge in children when used in the context of
a general health curriculum.34 Asthma Command has
been evaluated in clinic settings where children who
used the program showed increases in knowledge and
in self-reported asthma management, compared with
children in the control group.35 There were no demonstrated differences in visits to physicians, emergency
rooms, or hospitals.
Although these trends are encouraging, there
remains a need for programs that can be tailored to
the asthma characteristics of the individual child and
that can help patient and families learn self-management skills. We describe here such a program,
WDTA, a second-generation asthma CAI program
that has been rigorously evaluated.3
Watch, Discover, Think and Act
Computer-assisted Instruction
The WDTA computer-based education program has
taken a motivational approach to teaching asthma
self-management skills to urban, minority children.1–3 The program is a multimedia application
that uses three types of computer-based instructional
strategies—a simulation of real-world activities in
which the child can learn and practice self-regulatory
processes; tutorials with which the child can learn
and practice asthma-specific skills; and a game treatment to enhance motivation. The broad objectives of
the program are to provide asthma self-management
skills training as an adjunct to medical care and
enhance clinical care provided for the asthma patient
by supplying information to health care providers
and parents regarding the child’s asthma self-management capabilities and progress.
The program specifically targets change in factors
that may be determinants of this self-management.
The program was developed using social cognitive
theory change methods to improve the child’s knowledge, self-efficacy, and attributions.37 These methods
include verbal reinforcement, guided practice with
feedback, persuasion, goal setting, incentives, and
symbolic modeling. The program addresses the need
51
to individualize asthma education and to teach selfregulatory skills, components of what Creer et al.38
refer to as a second generation of asthma self-management programs.38
Overview of the Game Procedure and
Graphical User Interface
Watch, Discover, Think and Act is an interactive multimedia computer program for providing intensive,
tailored self-management education to inner-city
children, of upper elementary and middle school
ages, who have asthma. Designed for use in primary
care clinics and physician’s offices, it gives these children the opportunity—in a safe, non-threatening,
even fun, computer environment—to learn how to
manage their asthma .
Originally developed on CD-ROM for the Apple
platform, using MacroMind Director 5.0 authoring
software,39 WDTA makes use of text, graphics, animation, sound, and video clips.
The program comprises four stages—data input,
introduction, game scenarios, and data output. The
first use of the program occurs after the encounter
with the physician. A clinic staff member helps the
child with data input, using the keyboard and mouse
to provide information about the child’s physician
and about the child, such as name, age, and duration
of asthma. Information on personal asthma symptoms and environmental triggers, medications, and
peak flow make up the child’s asthma profile.
Once this information has been entered, the child
self-navigates through the program using the mouse.
During the introduction stage, the child chooses a
character and a coach. The character represents a
child approximately 12 years old who has asthma.
The child can choose whether the character and
coach are male or female and can choose between
African American and Hispanic ethnicity. The coach
is a teenager, slightly older than the target population
for the game, who has learned to manage asthma.
The child is given an overview of the game, which
involves a mission to rescue plans for anti-pollution
technology from the castle of Dr. Foulair. The goal of
the game is to move the character through three reallife scenarios with multiple scenes (home, school, and
neighborhood) and then to Dr. Foulair’s castle. To
progress from one scenario to the next, the child must
successfully manage the character’s asthma by following the four self-regulation steps of watching (monitoring symptoms and environmental triggers, taking
maintenance or preventive medication, and keeping
52
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
Figure
1 Watch,
Discover, Think and
Act computer game
screen.
appointments), discovering (deciding whether an
asthma problem exists and what its probable cause is),
thinking (deciding on a list of possible actions), and
acting (choosing an action such as taking rescue or
symptom relief medicine, removing or avoiding triggers, getting help). The child must also collect mission
handbook pages to complete tutorials on asthma and
click and drag tools to be used in the castle.
The game scenarios include 18 real-world and 4 castle situations that present the problems that innercity children with asthma must deal with successfully to manage their disease. The game screen
shown in Figure 1 shows one of the scenario scenes
containing environmental asthma triggers (dust,
fur, and feathers), tools (the peak flow meter in the
table drawer), and mission handbook tutorial pages
(on the bookshelf). Tutorial components contain
information developed de novo as well as components drawn from National Institutes of Health
source material.40,41 In the tutorials, video segments
depicting medicine-taking procedures were
obtained by permission to use pre-existing educational materials.42
In Figure 1, four self-regulatory icons for WDTA are
vertically aligned to the right of the scene, near the
center of the screen. Below these, a fifth icon represents a cellular phone with which to contact the coach.
The health status boxes on the far right of the screen
show the character’s symptoms, peak flow, medication taking, appointment scheduling, and personal
triggers; they appear during the “watch” step of the
asthma self-management process. The WDTA pro-
gram tracks each child’s progress so that children can
resume the game where they left off on a previous
visit.
The data output stage provides information for the
child, the parents, and the health care provider.
Players receive constant feedback from the game as to
their progress, and at the end of each session children
receive a certificate that congratulates them on the
progress made and reiterates the four steps of self-regulation. To guide further asthma education, the parents and physician receive a progress report that indicates the scenario the child reached, the child’s use of
the self-regulation steps, and tutorial scores.
METHODS
Design and Sample
A prospective pretest posttest trial with randomly
assigned intervention and comparison subjects was
used for the study. The WDTA program was evaluated in terms of its effect on cognitive impact variables
of knowledge, self-efficacy, and attribution; factors
associated with successful asthma management. The
hypothesis was that children using the intervention
would experience improvement in these cognitive
variables. A sample of 76 children was recruited from
six clinics and seven schools in a large urban area.
Five subjects were lost to posttesting because of lack of
availability for follow-up (n = 4) and refusal to participate further (n = 1). The resulting study sample comprised 71 children who were 8 to 13 years old and had
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
been diagnosed as having asthma by their health care
providers. The mean age of subjects in the study was
10.7 years. Forty-six boys and 25 girls completed the
posttest. Based on subject self-report, the study sample
was primarily white non-Hispanic (47.9 percent) and
African American (40.8 percent). The remaining five
children were Hispanic (11.3 percent).
Intervention and Data Collection Protocol
Children were recruited over ten months and assigned
to intervention or comparison groups after parents
gave written consent and children signed assent
forms. The children in the intervention group received
intervention in the form of playing WDTA, and those
in the comparison group received no intervention.
Data for each subject were collected in three sessions
over a three-week period. Sessions were held on a university campus affiliated with a large medical center.
Baseline data were collected from all children in session one. Measures included paper-and-pencil assessments of knowledge, self-efficacy, and attributions
regarding asthma self-management.
Session two for each subject occurred one week after
session one. In session two, children in the intervention group independently used WDTA. Following
children’s completion of the program instructions,
the investigator assessed each learner’s comprehension and provided further orientation to ensure
understanding of how to use the program correctly.
The children progressed through the first three levels
of the program. At the end of the third level, the
investigator asked the children whether they wanted
to continue to the fourth level or to stop using the
program. Process data of achievement and time on
task was collected in this session. Children in the
comparison group received no intervention in the
second session and were not required to spend time
at the study site. Session three occurred one week
later. In this session, posttest data were collected
from each child. In addition to the measures previously listed, these data included attitudes toward
computer-assisted instruction.
Measurement
For data collection, a pencil-and-paper format was
used and questionnaires were given to each subject
or parent (depending on the instrument) to complete
without assistance. However, the investigator
observed children completing example items of each
questionnaire to ensure that they understood the
instructions before they proceeded.
53
Child Knowledge of Asthma Management
Knowledge was assessed in two ways—by a questionnaire and by three open-ended questions. The Child
Knowledge of Asthma Management Questionnaire
was developed to assess change in knowledge in children between 7 and 12 years old and was based on the
educational objectives of the design document for
WDTA. Each item provided the child with a statement
about asthma self-management and possible responses of “yes,” “no,” and “don’t know.” The instrument
was pilot-tested on a study sample of 101 children
who had diagnoses of asthma. In the pilot sample, the
Cronbach coefficient alpha for the 30-item questionnaire was 0.86 for children 7 to 13 years of age, and
scores ranged from 5 to 30. The mean was 20.4 (±6.1),
and skewness was –0.99 (SE skew, 0.26). In a clinical
study involving 171 urban children with asthma who
were 7 to 16 years of age, the alpha was 0.73.2
At posttest, children were also asked three openended questions about strategies for asthma selfmanagement, and their answers were matched to a
set of possible correct responses. The questions (and
ranges of accurate responses) were as follows: What
are the four steps that you should follow to manage
your asthma? (0–4) What can you do to stop a problem before it starts? (0–10) What can you do to stop
an asthma problem after it starts? (0–16)
Child Self-efficacy for Asthma Self-management
Self-efficacy is the belief that one has the skill and ability necessary to perform a behavior in a variety of circumstances and in the face of various obstacles.37 Selfefficacy was assessed using a 23-item questionnaire
developed to determine change in confidence in performing self-regulatory and asthma-specific behaviors
in children 7 to 12 years old. The questionnaire included confidence in monitoring symptoms, environment,
medicine taking, and health care use; confidence in
deciding whether there is an asthma problem; and
confidence in determining appropriate solutions and
acting on them. Pilot testing on 101 children with asthma revealed an internal consistency using a Cronbach
coefficient alpha of 0.88. In the intervention trial of 171
urban-dwelling children with asthma who were 7 to
16 years old, the Cronbach coefficient alpha was 0.77,
indicating acceptable internal consistence.2
Causal Attributions
Attributions relate to the belief that self-management
behavior is controllable and is subject to personal
effort.43 Attributions were assessed using a 22-item
questionnaire developed for this study to determine
54
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
change in causal attribution along the dimensions of
locus and stability in children 7 to 12 years old. The
item format was modeled on that used in the
Children’s Attributional Style Questionnaire, also
known as the KASTAN-R44 (N. Kaslow, personal
communication, 1994). For each item in the questionnaire, the child is provided with a positive or negative self-management outcome. The subject is asked
to imagine experiencing the outcome presented. An
example of a positive outcome is “you go camping
and have no asthma problems the whole time.” An
example of a negative self-management outcome is
“you always have breathing problems when you
swim.” Two stems accompany each outcome. The
child is asked to choose the stem that gives the best
reason why the event would happen to him or her.
For each item, one attribution dimension (i.e., locus
or stability) is varied while the other dimension is
kept constant. Pilot-testing of this questionnaire
determined coefficient alphas for the locus subscales,
which were 0.54 (success), 0.53 (failure), and 0.64
(combined). Coefficient alphas for the stability subscales were 0.70 (success), 0.67 (failure), and 0.74
(combined). The locus and stability subscales were
not significantly correlated (r = 0.14, P = 0.31).
and hospital services, school grades, and absenteeism
was also obtained. Parents also completed a six-item
severity scale, developed by Rosier et al.,46 which
classified severity as low, moderate, mild, or high.
The scale assesses number of episodes, coughing or
wheezing, and curtailment of activities. An item reliability of 0.89 has been reported by the developers of
the scale.46 In the intervention trial of 171 inner-city
children with asthma, the coefficient alpha for the
scale was 0.77.2
Attribution Classification
Children were asked to classify the four principal
self-management behaviors (taking care of asthma,
avoiding triggers, watching for symptoms, and taking medicine) in terms of the attributional dimensions of locus, stability, and controllability. Children
were provided with a self-management behavior
(e.g., taking medicine) and asked to check boxes on a
semantic differential scale. This instrument uses a
format based on Russell’s causal dimension scale,
which was developed to assess causal attribution
dimensions in adults.45 Scale items assessing perceptions of locus were “something other people do for
you or get you to do” vs. “something you do yourself.” Scale items assessing perception of control were
“something you cannot control” vs. “something you
can control.” Scale items assessing perception of stability were “something you sometimes do” vs.”something you always do.” The coefficient alpha for the
12-item scale is 0.75, based on baseline data from the
71 children in the current study.
The motivational impact of the WDTA (referred to as
intrinsic motivation) was assessed using methodology similar to that described by Parker and Lepper.47
In that study, children were given a choice of computer treatments that they could use. In the current
study, motivational value of the program was
assessed by determining the number of children continuing to the end of the program (level four) after
being given the option to stop using the program at
level three. Children were also asked to indicate on a
four-point Likert scale how much they liked the computer game, liked to work with it, and liked the story
that went with it. Possible responses ranged from “I
didn’t like it” to “I liked it very much.” In addition,
the children were asked to compare WDTA with
their favorite board game, computer game, and
school subject and with other asthma education they
had had, using a three-point Likert scale with categories of “less fun,” “as much fun,” and “more fun.”
The children were interviewed about the game and
asked what they would tell their best friend and
other children with asthma about the game.
Demographic and Health Information
Attitude toward Computer-assisted Learning
Demographic information was obtained from primary caregivers, who were asked about their child’s
medicines, personal best peak flow, asthma triggers,
and symptoms. Information on the use of emergency
Attitude toward computer-assisted instruction was
assessed with the Attitude toward Computer-assisted Learning scale by Askar et al.48 The scale consists
of ten items, scored on a three-point response scale—
Computer Experience
Children were also asked three questions about their
computer experience. Responses to a question about
how often they used computers ranged from “not at
all” to “a few times a day.” To find out what they
used computers for, the children were asked to check
all that applied from a list of eight common applications, such as word processing, games, and graphics
or art and to list other uses. The children indicated
where they used computers by checking all that
applied from home, school, and friend’s home and by
listing other locations.
Motivation
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
yes (3), sometimes (2), and no (1); the negatively
worded items are reversed to a positive direction for
scoring purposes. Askar et al. report the alpha reliability estimate of the total score to be 0.81.48
Process of Computer Use
Four characteristics of the child’s computer use were
collected—fidelity, time on task, tutorial score, and levels completed. The fidelity of program use was
observed by the investigator, who rated children on
seven categories using a five-point scale (never, rarely,
sometimes, usually, always). The categories were as follows: needing assistance; understanding the program
directions; following the WDTA self-regulatory
sequence; making appropriate decisions in the game
scenarios; engaging with the game scenarios; and
attending to the tutorial segments.
Data Analysis
Sample Size Estimates
Data from the pilot test of the Child Knowledge of
Asthma Management and the Child Self-efficacy for
Asthma Self-management questionnaires with 101 children 7 to 13 years of age with asthma were used to calculate sample size requirements. On the basis of these data
and predetermined estimates of alpha at 0.05 and power
at 0.80, a sample of 80 subjects was calculated to be adequate to determine a difference 0.4 SD between groups
using an analysis of covariance (ANCOVA) procedure.49
Statistical Analysis
The study sought to answer two questions: Is the
computer program intrinsically motivating for children who use it? Do those children exposed to the
computer program experience significantly greater
change in knowledge, self-efficacy, and attributions
than children who are not exposed?
To answer the first question, an 80 percent threshold
for wanting to continue playing the game beyond the
third level was set to indicate that the program was
intrinsically motivating. To answer the second question, separate 2 × 2 repeated-measures analyses of
variance were conducted to determine whether a significant change in knowledge, self-efficacy, and attribution had occurred in the intervention group compared with the comparison group. Analysis of covariance was conducted on the open-ended knowledge
questions, which were collected only at posttest.
Pretest scores from the Child Self-management
Knowledge Questionnaire were used as covariates
for this analysis.
55
RESULTS
Asthma Severity, Computer Use, and
Demographic Variables
Forty-six percent of the study population was classified as having moderate-to-severe asthma. Most of the
children in the study were reported by their parents as
receiving above-average grades at school, with 73 percent reporting typical grades of As and Bs. Another
23.9 percent of children’s parents reported their child’s
typical grades to be Bs and Cs. The children in the
study were also experienced with computers. One
third of the children in the study sample reported
using computers a few times a day, and 90 percent of
them reported using computers a few times a month.
Computers were used principally in the school (81.7
percent of the children) and the home (61.9 percent).
Computers were used for a variety of purposes,
including school projects (70.4 percent), games (63.4
percent), and word processing (56.3 percent). In the
study sample, 97.2 percent of caregivers had completed high school or had some college or a higher degree,
and most study subjects came from two-parent households (68.6 percent). Most primary caregivers reported
being employed full-time (67.1 percent), and 4.3 percent were employed half-time. Only 9.9 percent of the
study sample were Medicaid recipients.
Differences between Groups at Baseline
There were no statistically significant differences
between the two groups in any of the variables that
might have affected performance on the CAI program (Table 2). The groups were also compared on
mean impact variables at baseline. The mean score
for the knowledge pretest was found to be significantly greater in the intervention group (P = 0.027).
No difference was found for the other variables.
Motivational Value of Watch, Discover,
Think and Act
With respect to the intrinsic motivation of the program, all the children in the intervention group who
had time to do so (32 of 38) continued to use the program when told they could stop. This represents 84.2
percent of the sample and exceeds the 80 percent a
priori criteria set for the study. The six children who
did not proceed to the fourth level did not complete
the entire game because of time constraints but indicated that they would have continued to play if time
had permitted.
56
Table 2
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
percent). The children indicated that the WDTA program was as much or more fun than their favorite
board game (88.9 percent), computer game (72.2 percent), subject in school (91.6 percent), and other asthma education (91.7 percent).
■
Demographic and Severity Variables, by
Number (%), for the Total Sample,
Intervention, and Control Groups
Variable
Total Study
Population,
N = 71
Intervention Comparison SigSubjects,
Subjects
nifi-.
n = 38
n = 33
cance
Sex:
Male
46 (64.8)
25 (65.8)
21 (63.9)
Female
25 (35.2)
13 (34.2)
12 (36.4)
Hispanic
5 ( 7.0)
2 ( 5.3)
3 ( 9.1)
Asian
1 ( 2.6)
1 ( 2.6)
—
Black
29 (40.8)
16 (42.1)
13 (39.4)
White
34 (47.9)
17 (44.7)
17 (51.5)
Other
2 ( 2.8)
2 ( 5.3)
—
Low
11 (15.5)
5 (13.2)
6 (18.2)
Mild
27 (38.0)
13 (34.2)
14 (42.4)
Moderate
25 (35.2)
17 (44.7)
8 (24.2)
8 (11.3)
3 ( 7.9)
5 (15.2)
As & Bs
52 (73.2)
25 (65.8)
27 (81.8)
Bs & Cs
17 (23.9)
12 (31.6)
5 (15.2)
Cs & Ds
2 ( 2.8)
1 ( 2.6)
1 ( 3.0)
—
—
—
Few times/yr
7 ( 9.9)
3 ( 7.9)
4 (12.1)
Few times/mo
17 (23.9)
11 (28.9)
6 (18.2)
Few times/wk
24 (33.8)
12 (31.6)
12 (36.4)
Few times/day
23 (32.4)
12 (31.6)
11 (33.3)
b
0.24
Ethnicity:
0.53b
Asthma severity:
Severe
b
0.32
School grades:
0.27b
Program Effectiveness
With respect to the effectiveness of the program,
Table 3 presents pretest and posttest mean scores for
the impact variables. Knowledge posttest scores were
significantly higher than pretest scores for the study
sample (F1 = 37.87, P = 0.00). However, repeatedmeasures analysis of variance revealed no betweengroup differences in knowledge (F1 = 0.35, P = 0.55).
A posttest-only analysis was found to be significant
between the groups for the open-ended questions
about the four-step self-regulation process (F1 =
189.18, P = 0.00), prevention strategies (F1= 12.33, P =
0.00), and treatment strategies (F1 = 17.48, P = 0.00).
Because of the difference in baseline knowledge
between the groups, an ANCOVA analysis was conducted using pretest knowledge scores as the covariate. Children in the intervention group had significantly greater scores on the open-ended knowledge
questions than children in the comparison group
when we controlled for knowledge pretest scores (all
P < 0.01).
NOTE: Mean ages, in years (SD), were as follows: total study population, 10.69 (±1.14); intervention subjects, 10.92 (±1.17); comparison subjects, 10.42 (±1.06); signficance, 0.067a.
a
Two-tailed t-test.
b
Chi-square test.
Assessment of the self-efficacy change scores
revealed the existence of an influential data point
greater than three SD from the mean. Using the criteria provided by Stevens,50 this case represents an outlier. Subsequent analysis of the self-efficacy data was
conducted with and without the outlier in the study
sample. When the outlier was included (n = 71),
repeated-measures analysis revealed no difference
between the groups (F1 = 2.33, P = 0.13) with an
observed power of 0.325. When the outlier was omitted, a significant improvement in self-efficacy was
apparent (F1 = 4.45, P = 0.04), with an observed
power of 0.547. The influential case did not differ significantly from other cases on the other variables
tested.
No significant pretest-posttest difference was found
between the groups regarding attitude about using
computers as a learning medium. The children in the
intervention group showed increased positive attitudes toward computers following the intervention,
but this was not significant (P = 0.327). The children
indicated that they liked the game (91.1 percent) and
liked working with the computer (86.3 percent). They
also liked the story that went with the program (72.3
Analysis of the total score and subscale scores of the
Asthma Self-management Attribution Questionnaire
revealed no difference between the intervention and
comparison groups. However, the total score for
attribution classification revealed a significant difference between the intervention and comparison
groups; children in the intervention group exhibited
significantly more positive attributions with respect
to asthma self-management (F1 = 4.45, P = 0.04).
Observed power for this analysis was 0.548.
Computer
experience:
None at all
0.73b
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
Process Variables
Observations of the children’s progress on the computer program revealed that most did not require
assistance with the program (69.4 percent). This is
probably because standard help was provided to all
children at the beginning of the first scenario. Most
children (80.6 percent) followed the program directions. However, they tended to stray from the watchdiscover-think-act self-regulatory sequence. Sixty-six
Table 3
■
Pretest and Posttest Means for Impact Variables of
Knowledge, Self-Efficacy, and Attribution
percent of the children were observed to use the
process only sometimes, rarely, or never. Most children (64.6 percent) usually or always made appropriate game decisions in the scenarios, such as choosing
appropriate triggers and solutions to an asthma
problem or taking appropriate actions for an asthma
problem. Furthermore, most (91.7 percent) usually or
always understood and attended to the tutorials. The
children were observed to be always or usually
engaged in the game activities (97.2 percent). Most
(94.4 percent) were observed to usually answer the
tutorial questions correctly. This is reflected by the
children’s high achievement scores on the tutorial
questions; the mean scores for all tutorials were
greater than 87 percent.
Variable
Group
n
Pretest
Mean (SD)
Posttest
Mean (SD)
DISCUSSION
Knowledge
questionnaire
Intervention
Control
38
33
18.6 (±5.1)
15.7 ( ±5.8)
21.1 (±5.4)
17.8 (±6.3)
Attention, Motivation and Appeal
Knowledge:
Self-regulation Intervention
Control
38
32
—
—
3.3 (±1.3)
0.06 (±0.3)
Prevention
Intervention
Control
38
33
—
—
2.7 (±1.1)
1.8 (±1.0)
Treatment
Intervention
Control
38
33
—
—
2.7 (±1.4)
1.5 (±0.8)
Self-efficacy*
Intervention
Control
38
32
53.4 (±9.7)
51.6 (±9.7)
56.5 (±9.8)
51.5 (±10.7)
Locus (+)
Intervention
Control
35
32
2.6 (±1.0)
2.9 (±0.9)
2.9 (±0.9)
3.0 (±0.9)
Locus (–)
Intervention
Control
37
32
3.2 (±1.1)
3.3 (±0.7)
3.5 (±0.8)
3.6 (±0.7)
Locus
(Total)
Intervention
Control
35
32
5.6 (±1.8)
6.3 (±1.3)
6.4 (±1.6)
6.6 (±1.2)
Stability (+)
Intervention
Control
37
33
4.3 (±1.8)
4.2 (±1.8)
4.8 (±1.8)
4.5 (±1.7)
Stability (-)
Intervention
Control
36
32
4.8 (±1.7)
4.6 (±1.8)
5.0 (±1.7)
5.3 (±1.7)
Stability
(Total)
Intervention
Control
36
32
9.0 (±2.8)
8.8 (±2.3)
9.9 (±2.7)
5.3 (±1.7)
Attribution
classification
Intervention
Control
37
33
36.1 (±7.1)
35.3 (±7.9)
39.5 (±6.4)
36.5 (±6.7)
Attribution:
* Outlier removed.
57
A fundamental tenet of social cognitive theory is that
if learning is to occur, the learner must attend to what
is learned.37 This program’s ability to attract children’s attention and to keep them engaged in the
learning activity is encouraging. All the children in
the study wanted to continue to the end of the game,
and they remained fully engaged in using the program, even after periods as long as 2.5 hours. This is
even more compelling when we consider that the
children in the study were sophisticated computer
users. They compared the WDTA computer application favorably with other games and education programs they had used. Krendl and Lieberman’s
research in computer-based education51 suggested
that effects on motivation might be simply effects of
the novelty of the medium. Given that the computer
was not new to the children in this study, we could
not attribute the program’s success to novelty alone.
Children in both groups had very positive views of
using computers to learn.
Snyder and Palmer52 noted the potential for instructional designers to create intricate, involving, and
illustrated contexts into which educational activities
can be embedded. Proponents have noted the potential motivational advantages of such procedures,47,52–54
whereas opponents have viewed such developments
as “sugarcoated” instruction that is likely to produce
less lasting and less efficient learning.54 While the
debate over “edutainment” continues, it must be
acknowledged that although an education program
may maintain the attention of the learner, it is only a
first step in engendering change in the educational
variables the program is designed to affect.
58
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
Enhancement of Knowledge, Self-Efficacy
and Attribution
Children who used WDTA were able to provide a
more extensive array of behavioral strategies for asthma management. They were able to reiterate the components of a four-step problem-solving framework,
describe behavioral strategies to prevent asthma
episodes, and describe behavioral strategies to treat
asthma symptoms to a significantly greater extent
than those in the comparison group. The potential of
the WDTA computer program to positively influence
asthma self-management behavioral capability is further demonstrated by the between-group difference in
self-efficacy. Enhanced self-efficacy theoretically leads
to greater likelihood of the child attempting asthma
self-management at home and to greater persistence in
the endeavor.37 Confidence to carry out self-management behaviors was not altered in the comparison
group but improved significantly in the intervention
group. The simulated experience of successfully negotiating a series of asthma self-management situations
and performing simulated self-regulatory actions
could change a child’s self-perceived ability to perform these behaviors. The application provides a
number of methods to elicit self-efficacy change in
learners, including persuasion related to self-management actions, guided practice with corrective feedback, and social and symptom reinforcement for selfmanagement success.3
The application is also designed to elicit change in
attributions regarding asthma self-management
behavior. To engender a move to more internal attributions, the learner is provided with direct control
over the asthma self-management of a chosen character and is accompanied by an older peer coach who
persuades the character that asthma self-management is largely in his or her own hands. The coach
also demonstrates that self-management is based
largely on effort and is not subject to external authority figures or to circumstances that cannot be
changed. Repeated self-management experiences
and situations reiterate the message that self-management failure is due to unstable (changeable) causes, such as lack of effort or modifiable environmental
circumstances that can be managed in the future.
A significant group difference was apparent in how
children classified asthma self-management behaviors. Children who had used the computer program
classified the behaviors as more internal (“something
I do myself”), more controllable (“something I can
control”), and more stable (“something I always do”).
This movement in perceived attributions indicates a
move to feelings of greater autonomy in the children
using the computer program. This change in attribution is theoretically related to enhanced self-efficacy
and is important if these children are to be active
asthma self-managers.55,56
Taken together, these results suggest that the program can influence factors related to asthma selfmanagement. The strength of these findings should
be considered in light of the relatively small sample
size of 71 children.
Study Limitations
The study was limited because of the small sample
size and some measurement problems. The significant change in knowledge scores in both groups
points to the measurement instrument being a potential intervention in itself. This was a group of children
with above-average school grades and, perhaps,
above-average motivation. We might, therefore, predict some learning from noticing what they didn’t
know on pretest and seeking to find the answers.
Parallel forms of the Asthma Knowledge
Questionnaire might have provided a more stringent
test. Although WDTA was effective in affecting
behavioral determinants in a laboratory setting with
children of moderate socioeconomic status, the effectiveness of the program in changing outcomes in a
clinical setting of low-socioeconomic-status, predominantly minority children was unknown. The efficacy
of the program in a laboratory setting indicated that
a broader clinical-based study was warranted.
Effects on Self-management and Behavioral
Outcomes: Use in Clinical Settings
A subsequent prospective pretest-posttest clinical
trial with randomly assigned intervention and comparison subjects in four inner-city pediatric asthma
clinics provided information on how the program
might affect asthma self-management behavior.2 The
clinic sites served an inner city, primarily Medicaidrecipient (government-funded) population. Two sites
were affiliated with large teaching hospitals headed
by respiratory specialists with staffs of rotating fellows. The other two clinics were inner-city community sites staffed by pediatricians. Inclusion in the
study was voluntary. No sites refused participation.
The computers were mounted on trolleys for ease of
transportation. Clinic rooms or offices provided for
the children to play the game were isolated from the
distractions of clinic activity. Patients who met the
inclusion criteria—age (6 to 17 years), moderate-to-
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
severe asthma (as defined by their physicians),
English speaking (parents could be Spanish speaking), and no chronic disease other than asthma—
were invited by the research coordinator to participate. Patient participation was voluntary.
On the first visit the patient would see the physician
and then be introduced to the computer by research
staff for data entry and orientation. The first session
with the computer comprised data entry, orientation,
and play through at least one scenario game screen.
This session lasted approximately 40 minutes. The
intention was for the child to use the program unassisted; however, research assistants were available if
the child needed help. On subsequent visits to the
clinic, the children played the computer game for
approximately 30 minutes before seeing the physicians. The computer’s record keeping allowed the
children to continue the program from where they
left off. After each play session, the child and the
physician received printouts with reinforcing messages, a reminder of the self-regulatory process
taught, and the scores in the game. Research assistants completed the self-management sections of the
plan, and physicians completed the sections on medications and treatment for episodes. Children in the
comparison group continued to have regularly
scheduled clinic appointments.
Results of the outcome study in the clinical sites indicated that children who were older and those who
scored higher at pretest improved their knowledge of
how to manage asthma. Self-management improved
for intervention children who had a more conservative estimate of their self-efficacy at pretest and for
children with higher pretest scores. Children in the
intervention group had a lower rate of hospitalization, and there were differences in functional status
that suggest improvement for children in the intervention group. Use of the self-management program
was associated with a decrease in symptoms for
those children whose symptoms were milder.
Feasibility for Clinic Use
Support for asthma self-management must include
the participation of health care providers so that education can be individualized to the child’s treatment
regimen; getting this participation can prove challenging.57 Health care providers work under growing time constraints, and in the two evaluation studies, enlisting their participation was difficult. The
WDTA program is by no means a substitute for an
National Asthma Education Program–recommended
asthma action plan. Rather, the two work in concert.
59
The information from the child’s asthma action plan
is incorporated into the game parameters of WDTA,
and the program gives the child simulated experience in managing asthma according to his or her
plan. Optimally, the health care provider collaborates
with the family in creating an action plan and helps
them identify the child’s triggers. In our experience,
physicians usually fail to provide the action plan.
Wide dissemination of the program will require support, such as an implementation manual and training
to enable the health care team to incorporate the use
of the action plan and help the child use the computer game. An additional challenge is managing the
system. Although self-contained and easily maintained, the computer still requires staff to troubleshoot, enter data, and introduce the patient to the
program. The WDTA program was subsequently
withdrawn from the clinics pending ongoing evaluation of the system based on program modifications.
Program Modifications
The results of these two evaluation studies allowed us
to plan a second iteration of WDTA. Three major modifications were planned and executed. They were development of a version for younger children, increase in
the amount of guidance and feedback for the older children regarding their use of the self-regulatory processes, and development of Spanish-language versions.
Development of the Program for
Younger Children
We found that the instructions were not adequate to
allow the learners to go through the program on their
own. Another problem with the program was the
amount of detailed information offered in the tutorial
segments. Although the 9- to 13-year-olds in the
impact study remained engaged in these tutorials,
younger learners in the clinic-based study found the
information presented overwhelming. Furthermore,
the indicators of health status were too complex for the
younger children (ages 7 to 8 years). Therefore, a new
version was developed that incorporated a smaller
amount of tutorial information into the simulations,
simplified the health status feedback, and provided
more coaching throughout.
More Guidance Regarding the
Self-regulatory Process
The observations that many children could not
explain the self-regulatory buttons and that some of
the children in the two evaluation studies tended to
not follow the four-step self-regulatory sequence in
60
SHEGOG ET AL., Evaluation of CAI Asthma Education Program
order prompted the development of increased program guidance, reinforcement, and control. In the
new version the children are guided to use watch,
discover, think, then act in that order, and they
receive more obvious score accrual for doing so.
Spanish Version
The WDTA program was developed for urban, lowincome children and was evaluated in the southwestern United States, where many children have Spanish
as a first language. Therefore, the second iteration
included a Spanish translation that was made using
both focus group methods to test possible translations of asthma-related words as well as the backtranslation method that has become the accepted
standard in health education.58 Currently, all versions of the program are being used and evaluated as
a part of a multi-component health-education and
health services program and evaluation study in 60
elementary schools in grades one through five.
Future Research
The primary recommendation, and next logical step,
for future research related to this and other technologically based programs is to conduct a diffusion study
to determine the best way to achieve dissemination,
adoption, implementation, and maintenance in clinics.
Additional research issues involve examining the
effect of parental asthma education on child behavior,
conducting an evaluation of the program outside clinics, examining the effects of providing further tailoring
in the program, evaluating the effectiveness of versions designed for younger children and for Spanish
speakers, examining the effect of the program on
patient–physician interaction, and adapting and evaluating the program for other diseases.
References
■
1. Watch, Discover, Think, and Act [computer program],version 1.02. Claverton, Md: Macro International Inc., 1995.
2. Bartholomew LK, Gold RS, Parcel GS, et al. Watch,
Discover, Think and Act: evaluation of computer-assisted
instruction to improve asthma self-management in innercity children. Patient Educ Couns. 2000;39:269–80.
3. Bartholomew LK, Shegog R, Parcel GS, et al. Watch,
Discover, Think, and Act: a model for patient education program development. Patient Educ Couns. 2000;39:253–68.
4. Halfon N, Newacheck PW. Childhood asthma and poverty: differential impacts and utilization of health services.
Pediatrics. 1993;91(1):56–61.
5. Taylor WR, Newacheck PW. Impact of asthma on health.
Pediatrics. 1992;90:657–62.
6. Crain EF, Weiss KB, Bijur PE, Hersh M, Westbrook L, Stein
RE. An estimate of the prevalence of asthma and wheezing
among inner-city children. Pediatrics. 1994;94:356–62.
7. Weiss KB, Gergen PJ, Wagener DK. Breathing better or
worse? The changing epidemiology of asthma morbidity
and mortality. Annu Rev Public Health. 1993;14:491–531.
8. Centers for Disease Control. Asthma mortality and hospitalization among children and young adults: United States,
1980–1993. MMWR Morb Mortal Wkly Rep. 1996;45(17):350–3.
9. Carr W, Zeitel L, Weiss K. Variations in deaths in New
York City. Am J Public Health. 1992;82:59–65.
10. Marder D, Targonski O, Orris P, Persky V, Addington W.
The effect of racial and socioeconomic factors on asthma
mortality in Chicago. Chest. 1992;101:426s–9s.
11. Targonski PV, Persky VW, Orris O, Addington W. Trends
in asthma mortality among African Americans and whites
in Chicago, 1968 through 1991. Am J Public Health.
1994;84:1830–3.
12. Weitzman M, Gortmaker S, Sobol A. Racial, social, and
environmental risks for childhood asthma. Am J Dis Child.
1990;144:1189–94.
13. Clark NM, Zimmerman BJ. A social cognitive view of selfregulated learning about health. Health Educ Res.
1990;5:371–9.
14. Bailey WC, Clark NM, Gotsch AR, Lemen RJ, O’Connor
GT, Rosenstock IM. Asthma prevention. Chest.
1992;102(3):216s–31s.
15. Thorensen CE, Kirmil-Gray K. Self-management psychology and the treatment of childhood asthma. J Allergy Clin
Immunol. 1983;72(5):596–610.
16. Clark NM, Rosenstock IM, Hassan H, Evan D, Wasilewski
Y, Feldman C, Mellins B. The effect of health beliefs and
feelings of self-efficacy on self-management behavior of
children with chronic disease. Patient Educ Couns.
1988;11:131–9.
17. Tobin DL, Wigal JK, Winder JA, Holroyd KA, Creer TL. The
“Asthma Self-Efficacy Scale.” Ann Allergy. 1987;59:273–7.
18. Wigal JK, Stout C, Brandon M, Winder JA, Creer TL,
Kotses H. The Knowledge, Attitude, and Self-efficacy
Asthma Questionnaire. Chest. 1993;104:1144–8.
19. Parcel GS, Meyer MP. Development of an instrument to
measure children’s health locus of control. Health Educ
Monogr. 1978;6:149–59.
20. Seligman MEP, Peterson C, Kaslow NJ, Tanenbaum RL,
Alloy LB, Abramson LY. Attributional style and depressive symptoms among children. J Abnorm Psychol.
1984;93(2):235–8.
21. Kuttner MJ, Delamater AM, Santiago JV. Learned helplessness in diabetic youths. J Pediatr Psychol.
1990;15(5):595–604.
22. Weiner B. An attributional theory of achievement motivation and emotion. Psychol Rev. 1985;92(4):548–73.
23. Paperny DM, Starn JR. Adolescent pregnancy prevention
by health education computer games: computer-assisted
instruction knowledge and attitudes. Pediatrics.
1989;l83:742–52.
24. Kann LK. Effects of computer-assisted instruction on
selected interaction skills related to responsible sexuality. J
School Health. 1987;57:282–7.
25. Meier ST, Sampson JP. Use of computer-assisted instruction in the prevention of alcohol abuse. J Drug Educ. 1989;
9:245–56.
26. Wetstone SL, Sheehan TJ, Votaw RG, Peterson MG,
Rothfield N. Evaluation of a computer-based education
lesson for patients with rheumatoid arthritis. J Rheumatol.
1985;12:907–12.
27. Starbright Foundation Web site. Available at:
Journal of the American Medical Informatics Association Volume 8 Number 1 Jan / Feb 2001
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
http://www.starbright.org/projects/sbw/index.html,
1999.
Williams RB, Boyles M, Johnson RE. Patient use of a computer for prevention in primary care practice. Patient Educ
Couns. 1995;25:283–92.
De Vries H, Brug J. Computer-tailored interventions motivating people to adopt health promoting behaviors: introduction to a new approach. Patient Educ Couns.
1999;36:99–105.
Huss K, Salerno M, Huss RW. Computer-assisted reinforcement of instruction: effects on adherence in adult
atopic asthmatics. Res Nurs Health. 1991;14:259–67.
Clubhouse Asthma [software]. Raleigh, NC: MindJourney
Software, 1999. Clubhouse Asthma Web site. Available at:
http://www.clubhouseasthma.com.
Wave Quest Inc. Bronkie the Bronchiasaurus [video
game]. Mountain View, Calif: Raya Systems Inc.,
1992–1995. Licensed by Nintendo, 1991.
The Wee Willie Wheezie asthma computer game [online].
Formerly available at GSF (National Research Center for
Environment and Health, Germany) Web site, at:
http://www.gsf.de/wjst/gamepage.htm, 1997.
Yawn BP, Algatt-Bergstrom PJ, Yawn RA, et al. An inschool CD-ROM asthma education program. J School
Health. 2000;70(4):153–9.
Rubin DH, Hecht AR, Marinangeli PC, Erenberg FG.
Asthma Command. Am J Asthma Allergy. 1989;2(2):108–12.
Lieberman DA. Interactive video games for health promotion: effects on knowledge, self-efficacy, social support,
and health. In: RL Street, WR Gold, T Manning (eds).
Health Promotion and Interactive Technology. Mahwah,
NJ: Lawrence Erlbaum, 1997.
Bandura A. Social Foundations of Thought and Action: A
Social Cognitive Theory. Englewood Cliffs, NJ: Prentice
Hall, 1986.
Creer TL, Kotses H, Wigal JK. A second-generation model
of asthma self-management. Pediatr Allergy Immunol.
1992;6:143–65.
Macromedia Inc. Macromind Director 5.0. Available at:
http://www.macromedia.com/software/director/.
National Asthma Education Program. Expert Panel
Report 2: Guidelines for the Diagnosis and Management of
Asthma. Bethesda, Md: NAEP, National Heart, Lung and
Blood Institute, 1997. Public Health Service report 97-4051.
National Asthma Education Program. Teach Your Patients
About Asthma: A Clinician’s Guide. Bethesda, Md: NAEP,
National Heart, Lung and Blood Institute, 1992. Public
Health Service report 92-2737.
Glaxo Wellcome, Inc. Managing Your Asthma:
Understanding Proper Inhaler and Peak Flow Technique.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
61
Research Triangle Park, NC: Glaxo Wellcome, Inc.
Publication GVL335R0.
Weiner B. An attributional theory of achievement motivation and emotion. Psychol Rev. 1985;92(4):548–73.
Seligman MEP, Peterson C, Kaslow NJ, Tanenbaum RL,
Alloy LB, Abramson LY. Attributional style and depressive symptoms among children. J Abnorm Psychol.
1984;93(2):235–8.
Russell D. The causal dimension scale: a measure of how
individuals perceive causes. J Pers Soc Psychol.
1982;42:1137–45.
Rosier M, Bishop J, Nolan T, Robertson CF, Carlin JB,
Phelan PD. Measurement of functional severity of asthma
in children. Am J Respir Crit Care Med. 1994;149:1434–441.
Parker LE, Lepper MR. Effects of fantasy contexts on children’s learning and motivation: making learning more
fun. J Pers Soc Psychol. 1992;62(4):625–33.
Askar P, Yavuz H, Koksal M. Student’s perceptions of
computer assisted instruction environment and their attitudes towards computer-assisted learning. Educ Res. 1992;
34:133–9.
Cohen J. Statistical Power Analysis for the Behavioral
Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum, 1988.
Stevens J. Applied Multivariate Statistics for the Social
Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum, 1988.
Krendl KA, Lieberman DA. Computers and learning: a
review of recent research. J Educ Comput Res. 1988;4(4):
367–89.
Snyder T, Palmer J. In Search of the Most Amazing Thing:
Children, Education and Computers. Menlo Park, Calif:
Addison-Wesley, 1986.
Loftus GR, Loftus ER. Mind at Play. New York: Basic
Books, 1983.
Bowers CA. The Cultural Dimensions of Educational
Computing: Understanding the Non-Neutrality of
Technology. New York: Teachers College Press, 1988.
Bandura A. Self-efficacy: The Exercise of Control. New
York: WH Freeman, 1997.
Skinner CS, Kreuter MW. Using theories in planning interactive computer programs. In: Street RL, Gold WR,
Manning T (eds). Health Promotion and Interactive
Technology: Theoretical Applications and Future
Directions. Mahwah, NJ: Lawrence Erlbaum, 1997.
Developing and implementing educational strategies and
interventions for controlling asthma in inner city and high
risk populations: final report. Claverton, Md: Macro
International Inc., 1994. National Heart, Lung and Blood
Institute contract N01-H0-39220.
Marin G, Marin BV. Research with Hispanic Populations.
Newbury Park, Calif: Sage, 1991.