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Journal Club Article
See page 49 for suggested questions to begin
discussion in your journal club.
A Randomized, Clinical Trial of Education
or Motivational-Interviewing–Based Coaching Compared
to Usual Care to Improve Cancer Pain Management
Mary Laudon Thomas, RN, MS, AOCN®, Janette E. Elliott, RN-BC, MS, AOCN®,
Stephen M. Rao, PhD, Kathleen F. Fahey, RN, MS, CNS, Steven M. Paul, PhD,
and Christine Miaskowski, RN, PhD, FAAN
D
espite important advances in its management, cancer pain remains a significant clinical problem (Apolone
et al., 2009; McGuire, 2004; van den
Beuken-van Everdingen et al., 2007). In
a meta-analysis, cancer pain was found in 64% of patients with metastatic disease, 59% of patients receiving
antineoplastic therapy, and 33% of patients who had
received curative cancer treatment (van den Beukenvan Everdingen et al., 2007). Cancer pain also has a
negative effect on patients’ functional status (Ferreira
et al., 2008; Holen, Lydersen, Klepstad, Loge, & Kassa,
2008; Vallerand, Templin, Sasenau, & Riley-Doucet,
2007) and is associated with psychological distress
(Cohen et al., 2003; Vallerand, Hasenau, Templin, &
Collins-Bohler, 2005). The effect of cancer pain on an
individual’s quality of life (QOL) can be significant
and extend beyond disturbances in mood and physical
function (Burckhardt & Jones, 2005; Dahl, 2004; Fortner
et al., 2003).
Although advances in pain management can reduce cancer pain for a significant number of patients,
numerous clinician, healthcare system, and societal
barriers (e.g., knowledge deficits, reimbursement and
regulatory constraints, religious or cultural views)
contribute to ineffective pain management (Brockopp
et al., 1998; Dahl, 2004; Hill, 1993; Sun et al., 2007). Attitudinal barriers held by patients can be a substantive
factor in the inadequate treatment of cancer pain (Anderson et al., 2002; Ward et al., 2008). Those attitudinal
barriers need to be addressed if cancer pain management is to be improved (Fahey et al., 2008).
In a meta-analysis of the benefits of patient-based
psychoeducational interventions for cancer pain management, Bennett, Bagnall, and Closs (2009) concluded
Oncology Nursing Forum • Vol. 39, No. 1, January 2012
Purpose/Objectives: To test the effectiveness of two
interventions compared to usual care in decreasing attitudinal barriers to cancer pain management, decreasing
pain intensity, and improving functional status and quality
of life (QOL).
Design: Randomized clinical trial.
Setting: Six outpatient oncology clinics (three Veterans Affairs
[VA] facilities, one county hospital, and one community-based
practice in California, and one VA clinic in New Jersey)
Sample: 318 adults with various types of cancer-related pain.
Methods: Patients were randomly assigned to one of three
groups: control, standardized education, or coaching.
Patients in the education and coaching groups viewed a
video and received a pamphlet on managing cancer pain.
In addition, patients in the coaching group participated in
four telephone sessions with an advanced practice nurse
interventionist using motivational interviewing techniques
to decrease attitudinal barriers to cancer pain management.
Questionnaires were completed at baseline and six weeks
after the final telephone calls. Analysis of covariance was
used to evaluate for differences in study outcomes among
the three groups.
Main Research Variables: Pain intensity, pain relief, pain
interference, attitudinal barriers, functional status, and QOL.
Findings: Attitudinal barrier scores did not change over time
among groups. Patients randomized to the coaching group
reported significant improvement in their ratings of painrelated interference with function, as well as general health,
vitality, and mental health.
Conclusions: Although additional evaluation is needed,
coaching may be a useful strategy to help patients decrease
attitudinal barriers toward cancer pain management and to
better manage their cancer pain.
Implications for Nursing: By using motivational interviewing techniques, advanced practice oncology nurses can help
patients develop an appropriate plan of care to decrease pain
and other symptoms.
39
that, compared to usual care, educational interventions
improved knowledge and attitudes and reduced average and worst pain intensity scores. However, those
interventions had no effect on medication adherence or
in reducing pain’s level of interference with daily activities. Bennett et al. (2009) suggested that additional trials
are warranted to test different approaches to cancer pain
education and to clarify the exact relationships between
education and improved patient outcomes.
Many psychoeducational intervention studies were
conducted in the hospital setting (Chang, Chang, Chiou,
Tsou, & Lin, 2002; de Wit et al., 2001; Jahn et al., 2010) or
in patients’ homes (Given et al., 2002; Miaskowski et al.,
2004), which limited the generalizability of the findings
to the outpatient clinic setting. In addition, although
they achieved a positive outcome, many of the studies
were labor-intensive, which also limited their ability to
be implemented in a busy oncology clinic (Given et al.,
2002; Miaskowski et al., 2004). Unfortunately, studies
using less labor-intensive interventions were not as
successful in decreasing cancer pain (Anderson et al.,
2002; Oliver, Kravitz, Kaplan, & Meyers, 2001; Syrjala
et al., 2008).
Coaching is a useful strategy to improve cancer pain
management (Kalauokalani, Franks, Oliver, Meyers, &
Kravitz, 2007; Miaskowski et al., 2004). Incorporating
principles of motivational interviewing into a coaching
intervention affords a unique method of exploring personal attitudes, behaviors, and beliefs that can interfere
with effective cancer pain management (Fahey et al.,
2008; Prochaska & DiClemente, 1984).
Change theory, specifically the Transtheoretical Model
(Prochaska & DiClemente, 1984), is a useful conceptual framework for coaching. In this model, behavioral
change is a function of a person’s state of readiness or
motivation to modify a particular behavior. Motivational interviewing is a nonauthoritarian counseling
technique that can assist patients in recognizing and
resolving ambivalence about making constructive behavioral changes. It matches the patients’ readiness to
change and can motivate the patient to move through
the stages of the Transtheoretical Model: precontemplation (unaware of need for change), contemplation
(thinking about change), preparation (actively considering change), action (engaging in changing behavior),
and maintenance (maintaining a changed behavior)
(Fahey et al., 2008; Prochaska & DiClemente, 1984).
Given the limitations of previous intervention studies,
additional research is warranted using approaches that
can be implemented in the outpatient setting. Therefore,
the purposes of this randomized clinical trial were to test
the effectiveness of two interventions compared to usual
care in decreasing attitudinal barriers to cancer pain
management, decreasing pain intensity, and improving pain relief, functional status, and QOL. The authors
hypothesized that the motivational-interviewing–based
40
coaching group would demonstrate greater benefit (i.e.,
decreasing attitudinal barriers; decreasing pain intensity; and improving pain relief, functional status, and
QOL) than either the conventional education or usual
care groups.
Methods
Sample and Settings
A convenience sample was obtained by recruiting
patients from six outpatient oncology clinics (three
Veterans Affairs [VA] facilities, one county hospital,
and one community-based practice in California, and
one VA clinic in New Jersey). Patients were eligible to
participate if they were able to read and understand the
English language, had access to a telephone, had a life
expectancy longer than six months, and had an average
pain intensity score of 2 or higher as measured on a 0–10
scale, with higher scores indicating more pain. Patients
were excluded if they had a concurrent cognitive or
psychiatric condition or substance abuse problem that
would prevent adherence to the protocol, had severe
pain unrelated to their cancer, or resided in a setting
where the patient could not self-administer pain medication (e.g., nursing home, board and care facility). The
study was approved by the institutional review board
and research committee at each of the sites. To test the
interaction of time (change in scores from pre- to poststudy) by assignment to the three treatment groups
(i.e., control, education, or coaching), a sample size of
240 was needed to detect a medium effect (f = 0.25; h2 =
6% of explained variance). As shown in Figure 1, of the
1,911 patients who were screened, 406 were eligible to
participate, 322 provided written informed consent, and
289 completed baseline assessments after being randomized to one of three groups.
Procedures
Prior to beginning participant recruitment, all research team members were trained extensively so
that the procedures for enrollment, data collection,
and interventions were standardized across all clinic
sites. Research associates (RNs or psychology interns)
were trained in procedures for evaluating potential
participants, approaching them, obtaining consent to
participate, and administering the instruments and
videotapes. Importantly, the research associates were
trained in providing attention-control telephone calls.
The nurse interventionist was trained extensively in
motivational interviewing and change theory by a
cognitive behavioral psychologist and then in procedures related to the specific coaching protocol. Details
of this training are described in Fahey et al. (2008).
Monthly team meetings were held throughout the
study to ensure procedural fidelity was maintained.
Vol. 39, No. 1, January 2012 • Oncology Nursing Forum
Patients and clinicians at the
study sites were blinded to the
patient’s group assignment.
At the time of enrollment, pa• Did not meet inclusion criteria (n = 1,505)
tients completed a demographic
• Declined to participate (n = 84)
questionnaire, the Karnofsky
Performance Status (KPS) scale
(Karnofsky & Burchenal, 1949),
Stratify (N = 322)a
the Brief Pain Inventory (Daut,
• Treatment (chemotherapy, radiation therapy,
Cleeland, & Flanery, 1983), the
or none)
Barriers Questionnaire (BQ)
• Pain (low, medium, or high)
(Ward et al., 1993), the 36-Item
Short Form Health Survey (SF36®) (Ware & Sherbourne, 1992),
Randomize into groups (N = 318)a
and the Functional Assessment
of Cancer Therapy–General
(FACT-G) (Cella et al., 1993).
Control (n = 109)
Education (n = 103)
Coaching (n = 105)
The patients’ medical records
were reviewed for disease and
treatment information.
Completed T1 (n = 104)
Completed T1 (n = 94)
Completed T1 (n = 91)
Patients in the usual care group
viewed a video on cancer (American Cancer Society, 1994). PaCompleted coaching
tients assigned to the education
intervention (n = 74)
group viewed a video on managing cancer pain that focused on
overcoming attitudinal barriers
Completed T2 (n = 88)
Completed T2 (n = 75)
Completed T2 (n = 64)
(Syrjala, Abrams, Du Pen, Niles,
a
Four patients withdrew before randomization, and one was lost to follow-up before completing T1.
& Rupert, 1995) and received the
Note. Reasons for lack of completion included being too ill, withdrawing, fatigue, being lost to
Agency for Health Care Policy
follow-up, death, ineligibility, prolonged hospitalization, protocol violation, or other.
and Research (1994) pamphlet
Figure 1. Trial Participation at Baseline (T1) and Six Months (T2)
entitled, Managing Cancer Pain,
Consumer Version, Clinical Practice
Guideline Number 9. To simulate
the time constraints in many oncology outpatient clinPatients were identified by clinic staff and screened
ics, no reinforcement of the material was provided
for eligibility by the research associate, who then apunless the patient sought additional information or
proached eligible patients, explained the study, and
asked questions of the clinic staff. Patients assigned
obtained written informed consent. Patients were stratito the coaching group received the same intervention
fied based on pain intensity (i.e., low, medium, or high)
as those assigned to the education group. In addition,
and cancer treatment (i.e., chemotherapy or radiation
they participated in four 30-minute telephone sessions
therapy) to control for the confounding variables of pain
that explored beliefs about pain, use of analgesics and
intensity and the effects of cancer treatment. Stratifying
nonpharmacologic pain management strategies, and
by pain intensity accounts for the curvilinear relationcommunication about pain management. Those four
ship between pain severity and functional status (e.g.,
calls were conducted about every other week over a
changes in pain intensity at the upper levels of the scale
six-week time period by the nurse interventionist, a
have a different effect on functional status compared to
clinical nurse specialist trained in motivational interchanges at the lower levels of the scale). Stratification
viewing techniques. For a detailed description of the
by cancer therapy was used to control for the effect of
coaching intervention, see Fahey et al. (2008). Patients
treatment in either decreasing pain from shrinking the
assigned to the usual care and education groups also
tumor or increasing pain because of toxicity of treatreceived four telephone calls (about every other week
ment. Patients at each clinic site then were randomized
over a six-week time period) from the research asbased on the stratification criteria using permuted
sistance for attention-control purposes. Six weeks
blocks with variable sizes into one of three groups: usual
after the final telephone call (i.e., 12 weeks postrancare (control), education, or coaching. This method of
domization), all patients completed the same quesrandomization was used to ensure balance across the
tionnaires that were done at enrollment. Participants
treatment groups within each stratification cell.
Assessed for eligibility (N = 1,911)
Oncology Nursing Forum • Vol. 39, No. 1, January 2012
41
received a $25 gift certificate after completing each set
of questionnaires.
The BQ has demonstrated adequate validity and reliability (Ward et al., 1993; Ward & Gatwood, 1994).
Pain was assessed with the Brief Pain Inventory, a
self-report instrument designed to assess the intensity
and quality of pain, the extent to which pain relief was
obtained, and the extent to which pain interferes with
function (Daut et al., 1983). Severity and interference
are rated on a numeric score from 0 (does not interfere)
to 10 (completely interferes). A mean interference score
was calculated (Serlin, Mendoza, Nakamura, & Cleeland, 1995), with higher scores reflecting greater pain
intensity and greater interference with function.
Functional status was measured with the SF-36
(Ware & Sherbourne, 1992). Eight health concepts
Instruments
Attitudinal barriers were assessed with the BQ (Ward
et al., 1993; Ward & Gatwood, 1994), a 27-item instrument
that measures eight barriers to cancer pain management
(concern about side effects, concern about tolerance, fear
of addiction, fatalism, fear of disease progression, desire
to be a good patient, fear of injections, and concern about
distracting the physician from curing disease). Each item
is rated on a scale from 0 (not at all agree) to 5 (agree very
much). Mean subscale and total scores were calculated
for the BQ, with higher scores reflecting stronger barriers.
Table 1. Demographic and Clinical Characteristics by Study Group
Characteristic
Age (years)
Education (years)
Time since diagnosis (months)
Karnofsky Performance Status scorec
Characteristic
Gender
Male
Female
Ethnicity
African American
Caucasian
Latino
Other
Marital status
Married or partnered
Widowed, divorced, or separated
Never married
Living arrangements
Alone
With family or friends
Other
Employment
Full- or part-time
Disability, leave of absence, or retired
Unemployed
Other
Cancer diagnosis
Breast
Colon
Head and neck
Lung
Myeloma
Prostate
Other (mixed types)
Control
(N = 88)a
Education
(N = 75)b
Coaching
(N = 64)
—
—
—
X
SD
X
SD
X
SD
Statistics
58.7
13.8
31.9
76.6
11.5
2.7
52.7
12.5
62.5
12.8
37.5
72.3
11.2
2.6
45
12.7
61.8
13.1
30
77.6
11.3
3.2
42.5
13.2
F(2, 223) = 2.54, p = 0.08
F(2, 222) = 2.57, p = 0.08
F(2, 222) = 0.48, p = 0.62
F(2, 222) = 3.53, p = 0.03*
n
%
n
%
n
%
Statistics
79
9
90
10
71
4
95
5
54
10
84
16
21
48
6
11
24
56
7
13
15
44
8
7
20
60
11
10
7
44
7
6
11
69
11
9
40
33
15
46
38
17
37
23
14
50
31
19
33
27
4
52
42
6
23
55
10
26
63
11
12
57
6
16
76
8
15
47
2
23
73
3
10
54
18
4
12
63
21
5
4
57
11
2
5
77
15
3
5
48
10
1
8
75
16
2
5
6
12
21
6
12
26
6
7
14
24
7
14
30
3
2
7
14
5
16
28
4
3
9
19
7
21
37
8
4
6
9
6
11
20
13
6
9
14
9
17
31
c2 = 4; p = 0.13
c2 = 13.4, p = 0.65
c2 = 8.3, p = 0.61
c2 = 6.4, p = 0.38
c2 = 10.1, p = 0.61
c2 = 45.7, p = 0.72
* Education < coaching, p < 0.05
a
Because patients could refuse to complete items, N = 86 for ethnicity and employment.
b
Because patients could refuse to complete items, N = 74 for ethnicity, marital status, and employment.
c
Scores indicate functional status on a 0–100 scale, with higher scores reflecting higher function.
Note. Because of rounding, not all percentages total 100.
42
Vol. 39, No. 1, January 2012 • Oncology Nursing Forum
Of the 289 patients who enrolled, 227 completed the
end-of-study evaluation. The length of time from cancer
diagnosis to study enrollment averaged 30–38 months.
The most common cancer types were lung, prostate, and
head and neck. Most patients were men and middleaged, and about half of the sample was married or
partnered. No differences were found among the three
groups on any demographic or clinical characteristic except KPS score. Patients in the education group reported
significantly lower KPS scores than patients in the coaching group (p = 0.03) (see Table 1).
Instrument Scores
Barrier Questionnaire: Barrier subscale scores were
modest in all three groups, with concerns about addiction
and disease progression rated higher than those related
to fatalism or the need to be a “good patient” (data not
shown). However, after controlling for each of the BQ
scores at baseline, no differences were found among the
three groups in any of the subscale or total BQ scores.
Pain intensity, interference, and relief: After controlling for average pain at baseline, no differences were
found among the three groups in average pain intensity
scores at the end of the study (p = 0.08) (see Figure 2).
Similarly, nonsignificant scores were found among the
three groups in worst pain intensity scores (data not
shown). However, significant differences were found
among the three groups in mean pain interference scores
at the end of the study (p = 0.01) (see Figure 3). Post-hoc
Average Pain Intensity
7
6
5
s
4
s
3
2
1
0
Baseline
Control
End of Study
s
s
Oncology Nursing Forum • Vol. 39, No. 1, January 2012
Sample
s
Differences in demographic and clinical characteristics among the three groups were evaluated using
analyses of variance and chi-square tests. Analyses
of covariance were performed to evaluate for differences in scores on average and worst pain intensity,
pain relief, mean pain interference, the BQ, the SF-36,
and the FACT-G among the three patient groups. That
procedure allows for the evaluation of the end-of-study
outcomes while controlling for those same outcomes at
baseline. The examination of differences among groups
in end-of-study outcomes, with baseline measurements
of those outcomes covaried out, often is a preferred
method for examining changes in outcome measures
from the beginning to the end of a study (Cohen, 1988).
All calculations used actual values. Adjustments were
not made for missing data; therefore, the cohort for
each analysis was dependent on the largest set of data
across groups. If the overall analysis of covariance for
a particular outcome indicated differences among the
three groups, pairwise contrasts were conducted to
determine the location of the difference. The Bonferroni procedure was used to distribute a family alpha
Results
ss
Data Analysis
of 0.05 across the three pairwise contrasts. All p values
have been adjusted so that values lower than 0.05 are
considered statistically significant.
s
were assessed (physical functioning, role limitations
because of physical health problems, bodily pain, social functioning, role limitations because of emotional
health problems, general mental health, vitality, and
perception of general health). In addition, physical and
mental component summary scores are obtained by
combining scores related to physical and mental functioning, respectively. For each scale, scores are reversed
(as needed so that higher scores reflect better health
states), summed, and linearly transformed on a 0–100
scale, with higher scores reflecting higher functioning.
The SF-36 has been used extensively and has wellestablished validity and reliability (Given, Given, Azzouz, Stommel, & Kozachick, 2000; McHorney, Ware,
& Raczek, 1993; Miaskowski et al., 2007; Thong, Mols,
Coebergh, Roukema, & van de Poll-Franse, 2009).
QOL was measured with the FACT-G (Cella et al.,
1993). Four QOL domains (physical, social, emotional,
and functional well-being) are measured. Patients
were asked to rate the extent to which they agreed
with each item using a five-point Likert-type scale
that ranged from 0 (not at all) to 4 (very much). Scores
for items within each subscale are summed to obtain
a subscale score, and all of the individual items are
summed to obtain a total score, which can range from
0–112. The FACT-G has been used in numerous studies
of patients with cancer (Elting et al., 2008; Wittmann,
Vollmer, Schweiger, & Hiddemann, 2006; Zimmerman
et al., 2010) and specifically in studies of patients with
cancer-related pain (Chang, Hwang, & Kasimis, 2002;
Harris et al., 2009). The FACT-G has well-established
validity and reliability (Cella et al., 1993).
Education
s
Coaching
Note. F = 2.58; p = 0.08
Figure 2. Changes Over Time in Average Pain
Intensity Scores by Patient Group
43
40
s
s
ss
30
s
—
50
s
X Pain Interference Scorea
60
20
Discussion
10
0
Baseline
End of Study
100
s
s
s
Baseline
End of Study
s
s
s
Pain Relief (%)b
80
60
40
20
0
s
s
Control
Education
s
Coaching
F = 4.53, p = 0.01; coaching > control, p = 0.02; coaching >
education, p = 0.03
b
F = 2.63, p = 0.07
Note. All values are plotted as means and standard deviations of
the mean.
a
Figure 3. Changes Over Time in Mean Pain
Interference and Pain Relief Scores by Group
contrasts demonstrated that the coaching group had
lower mean pain interference scores at the end of the
study compared to the education and control groups
(p = 0.03 and 0.02, respectively). After controlling for
baseline pain relief scores, no significant differences
were found among the three groups in the percentage
of pain relief (p = 0.07) at the end of the study.
Short-Form Health Survey: Table 2 lists the pre- and
post-study SF-36 subscale and component scores for the
three groups. After controlling for each of the baseline
SF-36 subscale and component scores, no significant
differences were found among the groups in social functioning, physical or emotional role functioning, bodily
pain, or physical component scores. However, after
controlling for each of the subscale scores at baseline,
significant differences were found among the groups in
general health, vitality, mental health, and the mental
component summary score. Post-hoc contrasts demonstrated that the coaching group had higher mental health
component scores compared to the control group. All
other post-hoc comparisons were not significant.
44
Functional Assessment of Cancer Therapy–General:
Table 3 lists the pre- and post-study subscale and total
QOL scores for the three groups. Scores for all four
subscales remained stable over time. After controlling
for each of the FACT-G scores at baseline, no significant
differences were found among the groups on any of the
subscale or total scores.
Educational interventions have demonstrated positive
outcomes in decreasing cancer pain (Clotfelter, 1999;
Dalton, Keefe, Carlson, & Youngblood, 2004; de Wit et
al., 2001; Syrjala et al., 2008; Ward et al., 2008; Yates et
al., 2004). Coaching has been tested less frequently as a
pain management intervention, but it resulted in positive outcomes in three studies (Kalauokalani et al., 2007;
Miaskowski et al., 2004; Oliver et al., 2001). Although successful, the labor-intensive nature of those interventions
may limit their use in clinical practice.
The current study tested the effects of two interventions
(standardized education and coaching) that were feasible
for implementation in an outpatient oncology clinic setting. The coaching intervention was designed to afford
flexibility for both the patient and the nurse interventionist to enhance its utility in clinical practice. Patients
assigned to the coaching group reported a statistically significant decrease in pain’s interference with function and
improved ratings of vitality, mental health, and general
health. Compared to standardized education, coaching
also was associated with clinical improvements in cancer
pain management (i.e., decreased cancer pain intensity
and improvement or stability in functional status and
quality of life). However, most of the improvements were
not statistically significant. Several possible explanations
exist for the lack of statistical significance for most of the
outcome measures.
The current study was unique in that the coaching intervention used principles of motivational interviewing
and was based on the Transtheoretical Model of change
theory. Those basic principles involve addressing issues
of greatest importance from the patient’s perspective and
assessing the individual’s readiness to change a particular
behavior. Some patients in the coaching group exhibited
persistent reluctance to consider changing a given attitude
or behavior that might result in improving their cancer
pain management. More commonly, the issue of priorities had a significant effect on the nurse interventionist’s
ability to address attitudinal barriers that might affect
cancer pain management. Cancer pain does not exist in
a vacuum. Other issues, related—or not—to cancer and
its treatment, often were more pressing from the patient’s
perspective. True to the theoretical underpinnings of the
intervention, the nurse interventionist, in turn, focused on
those more pressing issues. That adaptation posed challenges in adhering to the attitudinal content within the
Vol. 39, No. 1, January 2012 • Oncology Nursing Forum
study design was modified at the
request of the peer reviewers to
delay the post-test to six weeks
after the coaching intervention
was completed. In hindsight, anStatistics
other measurement should have
F = 1.179, p = 0.309
been made immediately after
the coaching intervention was
completed (six weeks after baseF = 2.817, p = 0.062
line), with a third measurement
at 12 weeks after baseline. The
F = 4.249, p = 0.015a
additional measurement would
have allowed for an assessment
F = 3.963, p = 0.02b
of the immediate effects of the
intervention, particularly with
patients who were able to comF = 3.207, p = 0.042c
plete the intervention, but died
or were too ill to complete the
F = 3.397, p = 0.035d
questionnaires at 12 weeks. If a
more significant effect was seen
immediately after completing the
intervention, but was not sustained, an argument could then
be made for providing some brief
ongoing sessions to reinforce the
coaching intervention.
In isolation, a behavioral intervention to decrease
cancer pain likely will demonstrate a small effect size.
Therefore, the lack of statistical significance may simply
be a reflection of inadequate sample size. The sample size
also was affected by a high attrition rate (30% of those
who enrolled to participate), often because of death or
disease progression, which could have contributed to
the lack of statistical significance in many of the outcome
Table 2. Short-Form Health Survey Scores by Study Group
Control
(N = 88)
Subscale
Physical functioning
Prestudy
Post-study
Body pain
Prestudy
Post-study
General health
Prestudy
Post-study
Vitality
Prestudy
Post-study
Mental health
Prestudy
Post-study
Mental component
Prestudy
Post-study
—
X
SD
42.4
37.3
Education
(N = 75)
—
X
SD
25.4
23.7
40.3
35
36.9
37.4
19
21.3
41.7
40.4
Coaching
(N = 64)
—
X
SD
27.4
25.3
43.5
42.2
27.9
29.2
32.5
38.4
16.2
23.4
33.9
43.2
20.6
21.8
21.5
22.9
41.4
35.3
19.3
18.2
47.8
47.4
23.6
24.3
34.7
32
18.9
19.7
35.5
30
20.8
19.5
37.1
39.3
21.2
22.7
64
63.6
20.6
19.3
62.3
62
21.2
22
66.3
70.8
19.4
20.4
42.5
41
11.9
12.1
41.6
41.1
12.6
12.5
43.3
45.7
11.8
12.1
Coaching > education, p = 0.016
Coaching > education, p = 0.02
c
Coaching > control, p = 0.089; coaching > education, p = 0.07
d
Coaching > control, p = 0.043
a
b
coaching protocol, but addressed the unique needs presented by the patient. Although the variation was viewed
very positively by patients in their study exit interview,
its effect on decreasing cancer pain likely was reduced.
Similarly, the researchers had difficulty maintaining
the attention-control telephone calls for their intended
purpose (i.e., to control for the attention received by
those in the coaching group). A substantial number
of patients (assigned to either
the education or control groups)
voiced significant problems or
Table 3. Functional Assessment of Cancer Therapy–General Scores
concerns to the research associate by Study Group
during those calls, which required
Control
Education
Coaching
the research associate to notify
(N = 88)
(N = 75)
(N = 64)
the patients’ clinicians. Although
—
—
—
X
SD
X
SD
X
SD
Statistics
such notification was important Subscale
from a clinical and ethical stand- Physical well-being
F = 1.373, p = 0.26
point, the patients did not seek
Prestudy
15.5
6.1
15.2
5.8
16.9
5.5
Post-study
15.7
5.7
15.5
6.1
17.6
6.2
intervention on their own, but
F = 0.465, p = 0.63
rather waited for support and as- Social well-being
Prestudy
19
6.3
20.2
6.1
21.1
5.4
sistance from the research associPost-study
19
6.4
19.3
6.3
20.5
6.1
ate beyond that offered from the
Emotional well-being
F = 2.41, p = 0.09
attention control design, which
Prestudy
16.7
5.3
16.7
4.7
16.5
5.6
Post-study
16.8
4.9
16.2
5.3
17.6
5.3
may have blunted the effects of
Functional well-being
F = 1.382, p = 0.25
the coaching intervention.
Prestudy
12.4
5.3
12.9
5.7
14.1
6.1
Another possible explanation
Post-study
12.8
5.7
12.3
5.8
14.4
6.4
for the current findings is that Total score
F = 2.164, p = 0.12
the coaching intervention yieldPrestudy
63.6
15.6
65.1
16.9
68.8
15.9
Post-study
64.4
16.3
63.3
17.5
70.5
17.3
ed a positive benefit, but the
benefit was not sustainable. The
Oncology Nursing Forum • Vol. 39, No. 1, January 2012
45
measures. In addition, more patients assigned to the
coaching group were unable to complete the end-ofstudy measures.
Another possible explanation for the lack of statistical
significance on many of the outcome measures is that
the instruments used were not sensitive enough to detect change. As a group, the sample scored low on each
barrier subscale and total score; the scores were similar
to those reported in other studies (Ward et al., 2008).
Although participants in the coaching group achieved
an improvement in each subscale (except fear of injections) that was greater than the improvement in the
other two groups, the differences were not significant.
Given the low baseline scores and smaller number of
patients assigned to the coaching group, the ability to
improve those scores would be extremely difficult. More
importantly, during the coaching telephone calls, unique
barriers were identified by the patients and discussed
that were not always reflected in the scores on the BQ
(Fahey et al., 2008). The strength of such beliefs or barriers may be so great that four coaching calls may have
been inadequate to overcome that enduring attitude. In
addition, motivational interviewing is based on change
theory, in which an individual’s readiness to change behavior is crucial to the success of a behavioral intervention (Prochaska & DiClemente, 1984). The current study
did not assess, nor stratify for, an individual’s readiness
to change a priori, which also could be a contributing
factor to those findings.
At baseline, the FACT-G subscale and total scores
in the current study were markedly lower than in the
general population, particularly the physical and functional well-being subscale scores (Holzner et al., 2004).
Similarly, functional well-being scores were lower than
those previously reported by patients with cancer
(Burckhardt & Jones, 2005; Sherman, Simonton, Latif,
Plante, & Anaissie, 2009). However, baseline scores for
all FACT-G subscales were similar to those obtained in
another study of U.S. Veterans with cancer pain (Chang
et al., 2002). QOL scores did not change substantially
over time in any group, which suggests that cancer
pain was not a significant factor in the QOL of those
patients. An alternative explanation is that the stability of scores may reflect the inability of the FACT-G to
detect subtle changes in QOL. Niv and Kreitler (2001)
acknowledge that pain can be an important factor in
one’s QOL, but also suggested that it may not always
be the most important. Therefore, focusing solely on
managing pain may not necessarily have a significant
effect on QOL. This view was substantiated in the
coaching group, in which other issues that affected
the patient’s QOL often took precedence over cancer
pain (e.g., those related to cancer treatment, family, or
economic hardship).
The SF-36 scores reported by patients in the current
study were lower than those reported by the general
46
U.S. population (Miaskowski et al., 2007; Wensing, Vingerhoets, & Grol, 2001) and other samples of patients with
cancer (Boini, Briançon, Guillemin, Galan, & Hercberg,
2004; Miaskowski et al., 2007; Mols, Coebergh, & van de
Poll-Franse, 2007; Wensing et al., 2001). Perhaps reflective of the supportive and alliance-building nature of
the intervention, scores related to mental health, mental component summary score, and even vitality and
social function improved from baseline in the coaching
group. In contrast, those scores declined in the other two
groups. As expected, physical functioning and general
health declined over time in the control and education
groups, yet surprisingly remained stable in the coaching group. Although bodily pain scores improved in
the coaching group (p = 0.06), attempts to improve
cancer pain management are unlikely to fully explain
all of those differences. However, the improvement may
better reflect the nurse interventionist’s willingness to
adapt to more pressing issues facing the patient during
the coaching telephone calls. That action is consistent
with motivational interviewing, but not captured by
standardized instruments.
Finally, the current study was not designed to alter the
amount and types of analgesics prescribed. The types and
amount of opioids prescribed and taken varied widely
among referral sites (Thomas, Annis, & Hwang, 2004).
Interestingly, in this subanalysis, the amount of opioids
prescribed or taken did not appear to affect pain intensity
ratings, pain relief, or satisfaction with pain management.
Although interventions that focus on medication use
alone also have not been consistently effective in controlling cancer pain, integrating pharmacologic interventions
with cognitive-behavioral interventions might produce
results that are more significant.
This study highlights the challenges of testing interventions that focus on clinical processes regarding provider advice, communication, and education in a severely
ill patient population. Those clinical processes often are
complex, and several interacting components may account for the outcomes. As a result, the authors encourage
the use of design methodologies and outcome measures
that address the complexities of clinical translational
studies and use of nonpharmacologic interventions.
Future studies should compare a coaching intervention
with different types of controls to ensure that the specific
effect of the intervention can be better distinguished from
those of other controlled factors, such as time, attention,
motivation, expectations, and experience (Bennett, 2010;
Bennett et al., 2009).
Conclusions and Implications
for Nursing Practice
Findings from the current study did not support
the use of mass-produced educational materials as an
Vol. 39, No. 1, January 2012 • Oncology Nursing Forum
effective means of managing cancer pain. However,
in the busy clinic setting, too often this approach is all
a patient with cancer in pain may receive. Symptoms
including cancer pain may not be carefully assessed,
nor interventions carefully selected, implemented, and
discussed. Advanced practice nurses (APNs) provide
comprehensive assessments of symptoms and problems faced by patients with cancer. Using motivational
interviewing, APNs and patients can jointly develop
an appropriate plan of care to decrease those symptoms. Motivational interviewing is a skill that can be
mastered by an APN with sufficient training. In working with patients over time, the use of motivational
interviewing can yield positive outcomes that extend
beyond traditional cancer pain management. Indeed,
the use of motivational interviewing is becoming more
popular as a mechanism to increase patient adherence
with medical treatment. Cancer pain management
needs to be addressed from an integrated biopsychosocial approach (e.g., pharmacologic, cognitive, behavioral, motivational, educational) for its effectiveness to
be achieved fully.
The authors gratefully acknowledge Marilyn (Marty) Douglas,
DNSc, RN, FAAN, who was coprincipal investigator of this study.
They also gratefully acknowledge the time and commitment on the
part of the patients who participated in this study.
Mary Laudon Thomas, RN, MS, AOCN®, is a hematology clinical nurse specialist and Janette E. Elliott, RN-BC, MS, AOCN®,
is a pain management clinical nurse specialist, both at the Veterans Administration Palo Alto Healthcare System in California;
Stephen M. Rao, PhD, is the health behavior coordinator and
director of the Training Psychology Postdoctoral Fellowship Program at the San Francisco Veterans Administration Healthcare
System in California; Kathleen F. Fahey, RN, MS, CNS, is the
palliative care coordinator at El Camino Hospital in Mountain
View, CA; and Steven M. Paul, PhD, is the principal statistician
and Christine Miaskowski, RN, PhD, FAAN, is a professor and
associate dean for Academic Affairs, both in the Department
of Nursing at the University of California, San Francisco. This
research was supported by the Department of Veterans Affairs,
Veterans Health Administration, Health Services Research and
Development Service (Project Number NRI-97026). The views
expressed in this article are those of the authors and do not
necessarily represent the views of the Department of Veterans
Affairs. Thomas can be reached at mary.thomas4@va.gov, with
copy to editor at ONFEditor@ons.org. (Submitted July 2010.
Accepted for publication May 17, 2011.)
Digital Object Identifier: 10.1188/12.ONF.39-49
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For Further Exploration
Use This Article in Your Next Journal Club Meeting
Journal club programs can help to increase your ability to evaluate the literature and translate those
research findings to clinical practice, education, administration, and research. Use the following questions
to start the discussion at your next journal club meeting. At the end of the meeting, take time to recap
the discussion and make plans to follow through with suggested strategies.
1.
2.
3.
4.
What is motivational interviewing?
How does motivational interviewing differ from counseling?
What is the purpose of having a control group? What was the intervention for the control group?
What is stratification and why was it important to stratify participants in this study based on (a) pain and (b)
cancer therapy?
5. In the discussion section of the article, the authors state, “Cancer pain does not exist in a vacuum.” What do
you think this means? How does this concept affect the efforts of the nurse to manage cancer pain?
6. In our practice, what types of nonpharmacologic resources do we provide to help patients manage cancer
pain? Do you feel these resources are effective? Why or why not?
Visit www.ons.org/Publications/VJC for details on creating and participating in a journal club. Photocopying of this
article for discussion purposes is permitted.
Oncology Nursing Forum • Vol. 39, No. 1, January 2012
49
Running head: RESEARCH CRITIQUE
1
Research Critique
SAMPLE 1
Stratford University
RESEARCH CRITIQUE
2
One of the obligation as a nurse is to use current best practice when caring for patients.
The nurse must be able to correctly appraise the research in order to confirm its dependability. In
order to verify the evidence-based practice, the study needs to be evaluated in varying degrees.
The article “Extending the Continuum of Care in Congestive Heart Failure” was written by
Austin, Landis, and Hanger and was published in the Journal of Nursing Administration in 2012.
This paper will appraise the writing style, author, title, purpose of the study, logical consistency,
literature review, theoretical framework, research question, sample, ethics, operational
definitions, methodology, analysis, results, and recommendations for the future study.
The study investigated the effect of an interactive voice response system (IVRS) and
clinical monitoring messages in patient’s self-management skill and its relationship with the
readmission rate in congestive heart failure (CHF) patients. Participants received IVRS messages
regarding self-management skills and were asked to answer a set of questions using a telephone
keypad. Participants who gained two pounds all contacted their physicians. This finding
indicated success in self-management. The readmission rate was reduced by fifty percent
compared to Roper hospital’s baseline heart failure patients. Currently, due to Hospital
Readmissions Reduction Program, the hospitals are now penalized when the readmission rates
exceed the national benchmarks (Austin, Landis, & Hanger, 2012). Thus, the effective selfmonitoring system is needed. The future research proposal will use this particular article in
answering the following clinical PICOT question: In older adult patients who have heart failure,
how does having a stand-alone integrated telemonitoring system compared to interactive voice
response system (IVRS) influence the rate of patient's readmissions over 6 months?
Overall, the article was well organized and written clearly to target a specific audience.
Austin et al. (2012) titled their research “Extending the Continuum of Care in Congestive Heart
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Failure: An Interactive Technology Self-management Solution”. Although it was quite long, it
was clear and accurate which enabled the audience to understand the main idea of the study.
However, the term ‘interactive technology’ or “IVRS’ was not clearly identified. Readers might
not be able to recognize that the IVRS was later called ListenUP! For health. When the
operational definitions are provided, it can enhance an audience’s understanding. Unfortunately,
the study does not clearly define any of the terms used.
In order to investigate reliability, each author was searched using Google. By visiting the
actual website, it was found that Dr. Austin was, in fact, the CEO of AudiaHealth. Her
involvement introduced bias and decreased intervention fidelity. She was a threat to the internal
validity. The fact that the article only mentioned her as an employer by AudiaHealth raised a
concern of trustworthiness of the study. On the other hand, the study was laid out in a logical
manner by providing an abstract, followed by research background, patient selection, study
design, results, discussion, and conclusion. These sequence of research process allowed the
article to flow naturally. In the beginning of the article, the authors clearly provided the purpose
of the study. They used the terms such as ‘tested’, ‘goal’, and ‘to determine’ to allow readers to
clearly identify their aim of the study (Austin et al., 2012). Authors described the objective of
their study in the abstract and also incorporated them into the introduction section. However,
because the research hypothesis was not clearly stated, it can cause confusion.
The literature review section was omitted in the article. A literature review can strengthen
the research article by providing gaps in the literature, supporting the research question, and
identifying the appropriateness of the methodology and data collection (Coughlan, Cronin, &
Ryan, 2007). Some authors incorporate the literature review into the introduction but it was not
presented in the introduction. The possible explanation could be due to lack of research being
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done on telehealth. Also, this study was a pilot program. Without the literature review, the article
failed to “demonstrate an appropriate depth and breadth of reading around the topic in question”
(Coughlan et al., 2007, p. 660). Since other studies were not evaluated through the process of the
literature review, the finding cannot be compared with other studies. Due to the absence of the
literature review, the article lacked some historical context and made it hard for readers to
visualize the study. Although the authors did not reference primary or secondary sources, they
did provide evidence of previous studies on interactive technology used in self-management.
They described the importance of patient compliance in reducing readmissions within the
introduction section of the article. The conceptual framework was not clearly stated in the article.
The authors did not link any theory that correlates with their study. There could have been a
restriction on the length of the article. Upon a brief search in the CINAHL database, the social
cognitive theory appeared to support the authors’ finding which implied that an increase in selfefficacy can enhance patient’s transition and self-care (Bandura, 1997).
From the total population of hundred twenty-four patients, sixty patients were targeted at
Roger Hospital. All participants were diagnosed with CHF and purposively selected by the unit
charge nurse, physician, and cardiologist to identify their qualification. The study started with a
total of seventy-two participants but twelve were lost after the discharge. When there is a small
sample size, the risk of sampling errors increase. The exclusion criteria for the study were clearly
stated and included diagnosis of dementia and participant who lives in assisted-living facilities.
Inclusion criteria included a primary diagnosis of CHF and possession of a telephone. Because
participants were selected by the researchers, it is considered non-probability sampling. Thus, the
findings lacked generalizability. The article could have been stronger if the samples were
collected in different locations. The ethical consideration was hard to determine because how the
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participants were informed about the research was excluded. Key ethical principles such as
autonomy and confidentiality need to be clearly identified in a research study. The article failed
to mention anything about patient harm, the principle of beneficence, HIPPA, and permission
from Ethics Service. The information about informed consent was missing from the article. Thus,
it was hard to note whether the participants’ confidentiality was guaranteed or not.
The research study itself was a pilot program and the research design was not clearly
outlined. Even though the article had its own research design section, the type of research design
was not made explicit in the article. By looking at the result, readers could assume that this was
quantitative research. They provided a figure to demonstrate their research design but it was
uncertain which type of quantitative study was used. Based on the article, it was most likely a
quasi-experimental design except participants were not randomly selected. The data was
collected daily in a remote location. According to the study, the set of clinical questions were
answered via telephone key pads and the data were stored electronically by ListenUP! For health
user interface (Austin et al., 2012). Then, the clinical staff reviewed the responses on a daily
basis. Within the method section, the authors did not fully describe the process of data collection.
Austin et al. (2012) provide what instruments were used within the study design section.
In order to verify the reliability and validity of the instrument used in their research, a brief
search on ‘ListenUP! For health’ was conducted in ProQuest which revealed forty seven results.
However, only one article was about this particular program. Thus, an additional search was
undertaken of the term ‘audiahealth’ which revealed twelve results. However, only one article
discussed this particular instrument and that information cannot be verified either because it was
not a peer-reviewed article. Also, the whole article consisted of the inventors quote regarding the
program. In addition, this study was a pilot program, where the design of the instrument was first
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introduced. Thus, validity and reliability of the instrument cannot be confirmed. Further study is
needed to ensure the validity and reliability of the findings.
The authors forgot to mention how the results were collected. In the results section of the
study, the authors did not clearly describe the analysis process. However, they discussed the
significance of the findings. They stated that the readmission rate was 10 percent which was
lower compared to Roper baseline CHF readmission rate, which was twenty one percent (Austin
et al., 2012). In the results section, the authors mentioned twelve participants lost during the
research process. Also, they analyzed different races and the average age. Austin et al. (2012)
reported that self-management skills were developed by IVRS as evidenced by the fifty percent
reduction in readmission rates. Also, they boasted that all participants who gained more than two
pounds were successful in calling their provider. They argued that these results support the
effectiveness of IVRS in a development of self-management skill which was critical in reducing
the number of readmission rate. The article discussed the limitations at the end. One of the
limitations the authors mentioned was the process of patient selection. They said that some
patients were suffering from a variety of diagnoses and this could have influenced the results.
Also, the study did not use a randomized controlled group. In addition, the results were only
compared against the Roper Hospital baseline for readmission rate.
For future studies the authors recommended performing a randomized trial in order to
investigate whether their positive results were due to selection bias (Austin et al., 2012). While
the authors did not specify the strength of their research, they concluded that the objective of the
study was adequately addressed. They described how an inexpensive IVRS can help in reducing
the readmission rate by improving self-management skill in CHF patients. In the references
section, every article and books used in the article were accurately stated.
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Reference
Austin, L., Landis, C., & Hanger, K. (2012). Extending the continuum of care in congestive heart
failure: An interactive technology self-management solution. The Journal of Nursing
Administration, 42(9), 442-6.
Bandura, A. (1997). Self-efficacy: the exercise of control. 1997, W.H. Freeman, New York.
Coughlan, M., Cronin, P., & Ryan, F. (2007). Step-by-step guide to critiquing research. Part 1:
Quantitative research. British Journal Of Nursing, 16(11), 658-663 6p.
Running head: CRITIQUE
1
Critique
SAMPLE 2
Stratford University
CRITIQUE
2
According to Alfes (2011), advancements in technology of healthcare are impacting the
way nursing education is being designed, delivered and evaluated (Alfes, 2011, p.89). The
expectation is for new nurses to transition into clinical practice as quickly as possible. New
nursing graduates are faced with several challenges as they enter clinical practice. One of the
major challenges include the inability to apply skills attained in a classroom setting into clinical
practice. For this reason, this writer wants to explore interventions that can be implemented
throughout nursing school to better prepare nurses in transitioning to clinical practice. The article
“Evaluating the use of simulation with beginning nursing students” written by Alfes (2011),
seeks to address the effectiveness of simulation as compared to traditional learning methods.
This paper will analyze the purpose, conceptual framework, literature review, methodology,
limitations, results, and validity of this research study.
The study compared the use of simulation at the beginning level of nursing programs
versus the traditional method of learning. First semester baccalaureate nursing students were
divided into two groups. One group used simulation and the second group used the traditional
learning methods. These two teaching methods were compared in regards to their impact on level
of self-confidence and learning satisfaction. The levels of self-confidence and learning
satisfaction were found to be higher with the nursing students that were involved in simulation
style learning. The findings of this article can be used as an intervention to enhance the process
of future research on evaluating the effectiveness of simulation lab. The findings from this
article can be used to support one aspect of the following clinical question: Does implementing
simulation lab in undergraduate nursing programs improve nurse competency and preparedness
for clinical practice compared to new graduate nurse residency programs within a year?
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The title of this study is appropriate and congruent with the content of the research study.
The title clearly identified the key variable, the use of simulation, as well as the population,
which was beginning nursing students. The abstract clearly summarized the purpose, methods,
sample size and conclusion of the research. In the introduction, the author clearly identified the
purpose of the study. The author acknowledged that while previous studies have documented the
effectiveness of simulation use for advanced clinical skills in more advanced level students, not
enough research has been conducted to test the effectiveness of simulation when implemented at
the beginning of the nursing curriculum (Alfes, 2011, p.89).
The purpose of the research was clearly stated as such “to compare the effectiveness of
using simulation versus a traditional learning method to promote self-confidence and satisfaction
with learning among beginning nursing students learning effective comfort measures” (Alfes,
2011,p.89). The purpose was imperative to the research study. It served as a guide to readers.
There were four different research questions mentioned by the author. The independent and
dependent variables are clearly stated. The beginning nursing students were the independent
variables. Self-confidence and learning satisfaction were the dependent variables. There was no
hypothesis stated as the purpose of the study was to compare different to interventions for
effectiveness. The author clearly states this research study was quasi-experimental.
The conceptual framework used in this research study was Kolb’s experiential learning
theory. Kolb’s theory was appropriate for this research. The research aligned with one of the
stages of Kolb’s experiential learning. Kolb’s active experimentation stage identified simulation
as a way for learners to translate knowledge attained into practice. The author successfully
supported the applicability of kolbs theory to the research study by citing primary sources.
According to Alfes, Kolb’s theory advocates for instructional programs that develops all types of
CRITIQUE
4
learners through different range of learning experiences in a variety of learning environments (
Alfes, 2011, p.89).
The literature review was extensive and comprehensive. It allowed the reader to
understand the study. The literature review provided support through primary sources that
simulation based learning was effective and also identified a gap in the study. It is also noted that
the best outcome was evident when simulation based learning was implemented in the beginning
of the nursing curriculum to the end. The reviewed literature mainly consisted of research
published within ten years from the publication year of study.
In methodology, the author listed steps taken to obtain an approval to conduct the study.
An approval for the study was obtained through the School of Nursing’s Center for Research and
the University’s Institutional Review Board (Alfes, 2011, p.91). This ensured that the study met
ethical standards. The issue of confidentiality was also addressed and stated as maintained
through the use of coding by laboratory session and learning strategy (Alfes, 2011, p.91). Even
though the inclusion criteria was not addressed specifically, it was stated that the sample of the
research consisted of first semester baccalaureate nursing students enrolled in a foundation of
practice course (Alfes, 2011, p.91). The author did not specify exclusion criteria for the control
or experimental group which hurts the internal and external validity but also the intervention
fidelity. In both the control and experimental group, the researcher did not consider prior health
care experiences of the students, which could have directly affected the outcome of this study. A
licensed practical nurse in a baccalaureate nursing program can pose a bias to the evaluation of
self-confidence due to prior clinical experience.
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5
The national league of nursing’s student satisfaction and self-confidence in learning
questionnaires was used as an instrument to evaluate the study results (Alfes, 2011, p.91). The
author stated that written permission was obtained from the national league for nursing to use
this tool. The reliability of the questionnaires was addressed by the researcher. “Reported
reliability for the questionnaire, with Cronbach alpha coefficients of 0.94 and 0.87 for the
satisfaction with currently learning and self confidence in learning subscales respectively”
(Alfes, 2011, p.91). However upon further research on the questionnaires used, it was found that
the NLN clearly stated that the use of student satisfaction and self-confidence in learning
questionnaire should be limited. The study on simulation has grown significantly since the
development of this instrument by the NLN in 2003. There are several current instruments that
the author could have selected. This affects the reliability of the outcome.
Result analysis showed that students that participated in simulation learning showed more
confidence statistically than those in a traditional learning group. With learning satisfaction, the
difference was not significant between the control and experimental group. The researcher stated
that the explanation for this finding might be due to the opportunities given to the control and
experimental group to be active participants in the learning experience. The participants were
able to ask questions and had the ability to equally receive feedback. The result analysis was
greatly detailed and addressed all four research questions.
Some limitations of the study were acknowledged by the researcher. The only areas
assessed were self-confidence and satisfaction with learning. This limits the translation of results
to performance outcome (Alfes, 2011, p.92). The author used convenience sampling which
subjects the study for risk of bias. Since convenience sampling was self-selecting
representativeness was also affected. The setting of the study was not clearly stated but it was
CRITIQUE
6
implied that it took place in a school. The time frame of the study was not mentioned. The name
of the nursing school was not mentioned however this could be due to confidentiality. The study
only represents a small sample of students from one school which affects the generalizability of
the study.
Overall, the research study was well organized and easy to comprehend. Further research
to explore the effectiveness of simulation as a learning strategy is needed to add to the strength
of this study. This research encouraged nursing programs to utilize technological advances in
health care and implement simulation based teaching at the beginners’ level to produce nurses
that are better prepared to take on the real world clinical patients effectively.
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References
Alfes, C. M., (2011). Evaluating the use of simulation with beginning nursing students. Journal
of Nursing Education, 50(2), 89-93.
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