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AMSTERDAM PREOPERATIVE ANXIETY AND INFORMATION SCALE VALIDATION STUDY

Authors:
  • University of Constantinus the Philosopher in Nitra - Univerzita Konštantína Filozofa v Nitre
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2 AMSTERDAM PREOPERATIVE ANXIETY AND INFORMATION SCALE: VALIDATION
STUDY
Jana Turzáková
Introduction
Most patients before a planned surgery experience significant anxiety. The prevalence of
anxiety prior to surgical procedures has been reported to range from 11% to 80% among
adult patient populations, with differences related to diagnosis or methods of measurement
(Maranets, Kain, 1999). The worries concern mainly fear of surgery and death, loss of
independence, separation from family, and postoperative pain (Caumo et al., 2001). Anxiety
is demonstrated as a complex experiential, behavioral, cognitive and neurobiological
phenomenon (Barlow, 2002). Long-term and untreated preoperative anxiety is accompanied
by physiological symptoms which can have adverse effects on patient‘s health (Vaughn et
al., 2007). Research shows that anxious patients may be at higher risk for pooperative
complications, they need longer period for recovery and experience higher levels of
postoperative pain (Kain et al., 2000). These patients report decreased comfort and quality of
life, show decreased compliance and decreased ability to make appropriate treatment
decisions (Caumo et al., 2001). In older patients who suffer from preoperative anxiety, even
higher morbidity and mortality are reported (Williams et al., 2013).
Considerable research has investigated the impact of various anxiety reducing interventions
prior to surgery, e.g. relaxation, medication, music (Bailey, 2010). One of the most
commonly implemented interventions is preoperative education. Providing information
should make the situation more predictable and less threatening and thus decrease anxiety,
but results are inconsistent (Vanečková, Vörösová, Sollár, 2011). Several studies have
concluded that providing patients with preoperative information has beneficial outcomes but
some authors report that providing information prior to surgery is associated with increased
anxiety in some patients (Stoddard et al., 2005). One of the possible explanations is related
to individual differences in coping when people face an uncontrollable stressor, the
confrontation with details is more anxiety provoking than anxiety reducing. The particular
dimension of coping that is relevant to this issue is information seeking versus information
avoidance (Miller, Mangan, 1983). In the face of the threatening situation, people differ in
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their use of coping strategies. Miller (1987) states that the impact of information on anxiety
is moderated by patients’ desire for information and proposes monitoring-blunting model
concerning the processing of health information. Patients cope differently with threatening
situations by either seeking out threat-relevant information to make events more predictable
(high monitoring) or by cognitively distracting from it preferring the event to remain
unpredictable (high blunting).
High monitors are characterized as those concerned about health risks, scanning for
potentially threatening health information and amplifying threatening cues. They tend to
experience more state anxiety during medical procedures and also demonstrate higher levels
of trait anxiety than blunters (e.g. Stoddard et al., 2005). Monitors tend to respond better to
more information and pay more attention to preventative health behaviors (Miller, 1996). On
the contrary, high blunters are characterized by postponing confrontation with potentially
threatening information, using defensive mechanisms of avoidance and denial (Miller, 1996).
Research shows that in medical conditions monitors and blunters cope better when amount
of and desire for information are matched, i.e. when monitors receive extensive information
and blunters only receive standard information concerning the upcoming procedure (Miller,
1996). When preoperative education is provided generally with no respect to these
differences, increased anxiety may be expected in monitors who are deprived of information
and blunters who are deprived of their desire to avoid information. The intervention may fail
to have positive effects on patients anxiety.
Therefore, it is important to assess patients anxiety and information need prior to
preoperative education to make sure the patient will be provided with a tailored intervention.
There are several instruments used for anxiety assessment in preoperative settings, e.g. the
Spielberger State Trait Anxiety Inventory (STAI, Spielberger, 1983), the Hospital Anxiety
and Depression Scale (HADS, Zigmond, Snaith, 1983), the Faces Anxiety Scale (FAS,
McKinley et al., 2003). However, only the Amsterdam Preoperative Anxiety and
Information Scale (APAIS, Moerman et al., 1996), which we validate in the study, combines
measurement of both anxiety and information need at once with only six items.
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Research objective
Assessment of patients anxiety and information need is crucial for planning interventions to
support patient‘s coping in the threatening situation. The Amsterdam Preoperative Anxiety
and Information Scale (APAIS) is a short and economic instrument aimed at assessing
patient‘s anxiety and information need. The aim of the study is to provide evidence of
APAIS psychometric properties. The APAIS was administered together with the
standardized self-report (STAI, HADS) and rating anxiety measurement tools (Anxiety
Level-12). Firstly we examine the factor structure of the APAIS to support the evidence of
its factor validity. Further, we investigate reliability of the scale for the purposes of the use
of the sum scores of Anxiety and Information Need subscales. Finally, we focus on
psychometric evaluation of the construct validity of the scale. We verify expected
relationships between the scores of the APAIS and standardized preoperative anxiety
measurement tools (STAI, HADS, Anxiety Level-12) and we examine expected differences
related to sex, type of surgery (planned or emergency) and previous experience with surgery.
Sample
The sample consisted of 60 patients (75% women) aged 22-84 years (M=57, SD=17).
Patients were admitted for surgery at one of the participating departments the Clinic of
Trauma Surgery and Orthopaedics and the Surgical Clinic. Time to operation ranged from
0:20 to 23:00 hours (M= 10:25, SD=8:52). Demographic and clinical characteristics of the
sample are presented in the Table 1.
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Table 1 Demographic and clinical characteristics of the sample
Dep. of Traumatology
and Orthopaedics
Surgical Clinic
Total
Patients
30
30
60
Male
15
0
15
Female
15
30
45
Planned surgery
16
30
46
Emergency surgery
14
0
14
No experience with surgery
21
30
51
Previous experience with surgery
9
0
9
Age AM (SD)
59.43 (15.50)
55.38 (18.06)
57.41 (16.81)
Methodology
Firstly the patients were explained the aim of the study and they signed their informed
consent. Then they were administered the set of measurement instruments: the Spielberger
State Trait Anxiety Inventory (STAI, Spielberger, 1983), the Hospital Anxiety and
Depression Scale (HADS, Zigmond & Snaith, 1983), the Amsterdam Preoperative Anxiety
and Information Scale (APAIS, Moerman et al., 1996). At the same time patients anxiety
was rated by the nurse on the 12-item rating scale Anxiety Level-12 (Solgajová, Sollár,
Vörösová, 2014). The instruments are described below in detail.
The Amsterdam Preoperative Anxiety and Information Scale was created in 1996 by Dutch
experts (Moerman et al., 1996) and since then it has been validated in Germany (Berth et al.,
2007), Japan (Nishimori et al., 2002) and France (Maurice-Szamburski et al., 2013) and has
been used in several research studies (e.g. Boker et al., 2002; Wattier et al., 2009). The
questionnaire consists of two scales, both the Anxiety scale and the Information Need scale
relate to the situation of waiting for the surgery. The instrument has 6 items rated by the
patient on a 5-point scale. The Anxiety score is calculated as the sum of items 1, 2, 4 and 5
and the need for information score is the sum of items 3 and 6. Authors (Moerman et al.,
1996) suggest a threshold score values valid for research and clinical purposes (with respect
to the risk of false positive and false negative result). The score above 11 for the Anxiety
subscale is a sign that the patient is experiencing anxiety and the intervention to reduce
anxiety is needed. Patients with the score 5 and higher in Information Need should be given
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the opportunity to get information about topics of concern, while the score less than 5 is a
sign that the patient should be provided with only basic information. Moerman et al. (1996)
present several advantages of the APAIS over similar measures of preoperative anxiety: it is
short, the items are easy to understand and apply for many healthcare settings, the
interpretation of results is simple. The APAIS is currently considered a valid, reliable and
practical tool for assessment of preoperative anxiety and information needs (Boker et al.,
2002; Nishimori et al., 2002), and is also useful for the purposes of screening (Berth et al.,
2007).
The State-Trait Anxiety Inventory by Spielberger et al. (1983) is a traditional self-report
questionnaire for evaluation of state and trait anxiety (Lam et al., 2005). In the study, only
the state subscale with 20 items rated on 4-point Likert-type scales was administered. The
scale measures the current state of anxiety how the individual feels right now, at this
moment. In most preoperative anxiety studies, the STAI is considered the “gold standard”
for anxiety assessment the best available method for determining the presence or absence
of anxiety (Mitchell, 2003).
The Hospital Anxiety and Depression Scale by Zigmond and Snaith (1983) is another well-
known tool for measuring the presence and severity of symptoms of anxiety and depression
in patients with physical illness with excellent case finding ability (Bjelland et al., 2002).
The questionnaire consists of 14 items; we administered only seven items measuring
symptoms of current state of anxiety, each with four possible answers.
The Anxiety Level-12 is a 12-item rating scale developed for use in nursing to screen for
patients who manifest anxiety. The anxiety indicators (sleep pattern disturbance, verbalized
anxiety, nervousness, crying, pounding heart, trembling, fear, difficulty concentrating,
irritability, concerns about future, increased pulse rate) are rated by the nurse on a 5-point
Likert-type scale. The scale was validated against the STAI and the HADS (Sollár et al.,
2014) and interrater reliability has been repeatedly successfully examined (Turzáková et al.,
2014). The nurses who administered the set of tools had an initial training and discussion on
the scale use and were provided with a manual explaining the meaning of the items of the
scales.
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Results
In the following section we present results of validation in detail. We present results on
factor validity, reliability a construct validity of APAIS (especially the convergent aspect).
Factor validity of the APAIS
In this section we report results of two factor analysis solutions for the APAIS. Results show
one-factor and two-factor solutions. At the end of this section, the comparison and
conclusion of these two solutions are offered. To make sure factor analysis is used
adequately before the application of the procedure, the values of the Correlation Matrix, the
Bartlett’s Test of Sphericity and Kaiser-Mayer-Olkin’s Measure of Sampling Adequacy
(KMO) were examined. In our dataset the Bartletts Test shows high significance (p< .001)
and the value of KMO=0.707 can be evaluated as good. For additional evaluation we assume
that n of observations (n=60) was also appropriate. It is a bit small sample but according to
the number of evaluated items (6) it can be concluded as appropriate. Results suggest that
conditions for the use of factor analysis are met what allows us to apply factor analysis to our
dataset.
Number of factors
Firstly several tables show the information about the number of factors. The most often used
method in determining the appropriate number of factors is to use Eigenvalues (usually set to
value greater than 1). According to this criterion one-factor solution was computed. Another
method in determining the number of factors is visual evaluation of the Scree Plot Graph.
The Scree Plot shows progressive reduction in the proportion of total variance explanation of
individual factors; the ideal number of factors is determined visually at a higher "break"
(severely diminished number of explanations of variance by a following factor). In our case,
the break is apparent after the first extracted factor (see Graph 1 below). When examining
the Eigenvalues, the second row reports the value just before the value 1 (.962). This was
also the reason for computing the two-factor solution.
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Graph 1 Scree Plot
Table 2 Total Variance Explained for two solutions (1F)
Component
1F
Initial Eigenvalues
Extraction Sums of Squared Loadings
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
70.017
70.017
4.201
70.017
70.017
2
16.037
86.054
3
8.456
94.510
4
3.002
97.513
5
1.330
98.843
6
1.157
100.000
Extraction Method: Principal Component Analysis.
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Table 3 Total Variance Explained for two solutions (2F)
Component
2F
Initial Eigenvalues
Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
4.201
70.017
70.017
3.250
54.161
54.161
2
.962
16.037
86.054
1.914
31.894
86.054
3
.507
8.456
94.510
4
.180
3.002
97.513
5
.080
1.330
98.843
6
.069
1.157
100.000
The tables above show how many components were included in the final factor solution. The
important information is what percentage of variance is explained by this component/factor.
In our case, one factor was extracted with total of 70% variability explained and two factors
were extracted with total of 86% variability explained (1st factor 54%; 2nd factor 31%). In the
next analyses, Communalities and Factor Loadings are evaluated.
Factor extraction
Factors were extracted by the method of the Principal Component Analysis (PCA). Varimax
rotation was used in the case of the two-factor solution. In this section values of
Communalities are reported. The communalities can range from 0 to 1; 0 indicates that the
joint factors do not explain any variance, and 1 indicates that whole variance is explained by
the joint factors. As can be seen later, the values are always high (all loadings for any of both
solutions are > .7).
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Table 4 Communalities for two solutions (1F, 2F)
Extraction
1F
Extraction
2F
I am worried about the anaesthetic.
.741
.822
The anaesthetic is on my mind continually.
.872
.902
I would like to know as much as possible about the anaesthetic.
.495
.876
I am worried about the procedure.
.808
.856
The procedure is on my mind continually.
.762
.845
I would like to know as much as possible about the procedure.
.523
.862
Factor matrix
In the next table Factor loadings for Components are shown. For the one-factor solution
Unrotated Components Matrix is reported and for the two-factor solution Rotated
Component Matrix is reported.
Table 5 Component Matrix
One-factor
Two-factor (Rotated)
Component
1
Component
1
Component
2
I am worried about the anaesthetic.
.861
.878
The anaesthetic is on my mind continually.
.934
.878
I would like to know as much as possible about the anaesthetic.
.703
.900
I am worried about the procedure.
.899
.874
The procedure is on my mind continually.
.873
.890
I would like to know as much as possible about the procedure.
.723
.881
In the factor matrix we can see that the first factor (in the one-factor solution) consists of all
variables; the minimal value of the factor saturation is .703. This result suggests that in the
background of all 6 items, there is only one latent factor (Table 5). However as we noticed
above (Eigenvalue of the second component close to value 1), we can see that in the two-
factor solution items with information seeking content load the second component. Loadings
are even higher than for the one-factor solution.
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Factor interpretation
The last phase of factor analysis is to interpret the extracted factor(s). This step requires
expertise (Sollár, 2014); in case of these results it is straightforward (partly because of the
number of items and partly because of the clear item content). The first factor in the two-
factor solution is anxiety and the second is information seeking. These results support
previous findings about the APAIS.
Reliability of the APAIS
The previous analyses show that the APAIS is not unidimensional but it has two dimensions.
In this part, reliability of two factors is evaluated by the Cronbach’s α and we present
detailed analyses. In evaluation of the description we can see that all 6 scale items were
responded to above the middle point of the 5-point scale, ranging from M=3.13 (The
anaesthetic is on my mind continually) to M=4.42 (I would like to know as much as possible
about the procedure).
Table 6 Description of the individual items and total scores of the APAIS (n=60)
M
SD
I am worried about the anesthetic.
3.68
1.186
The anesthetic is on my mind continually.
3.13
1.334
I would like to know as much as possible about the anesthetic.
3.95
1.171
I am worried about the procedure.
4.20
1.038
The procedure is on my mind continually.
3.58
1.293
I would like to know as much as possible about the procedure.
4.42
.907
The value of the Cronbach’s α for the evaluated scale (all 6 items) was .912. The individual
items of the scale correlate with the total scores ranging from r= .60 to r= .90 (Table 7,
Corrected Item-Total Correlation), which can be evaluated as very high. It can be seen in all
items that the Cronbach’s α practically does not change if an item is deleted.
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Table 7 Item-Total Statistics for evaluating reliability of items of the APAIS
Scale Mean
if Item
Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item Deleted
I am worried about the anaesthetic.
19.28
23.291
.792
.832
.889
The anaesthetic is on my mind
continually.
19.83
21.023
.896
.885
.872
I would like to know as much as
possible about the anaesthetic.
19.02
25.339
.598
.787
.917
I am worried about the procedure.
18.77
24.148
.836
.828
.885
The procedure is on my mind
continually.
19.38
22.410
.791
.828
.890
I would like to know as much as
possible about the procedure.
18.55
26.964
.634
.789
.911
The results of reliability evaluation suggest that the scale can be used as one-dimensional.
The value of the Cronbach’s α for the Anxiety subscale (4 items) was .943. The individual
items of the scale correlate with the total scores ranging from r= .83 to r= .91 (Table 8,
Corrected Item-Total Correlation), which can be evaluated as very high. It can be seen in all
items that the Cronbach’s α practically does not change if an item is deleted (all of them
lower the coefficient after deleting).
Table 8 Item-Total Statistics for evaluating reliability of items of the APAIS Anxiety
subscale
Scale Mean
if Item
Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
I am worried about the
anaesthetic.
10.92
11.874
.835
.788
.928
The anaesthetic is on my mind
continually.
11.47
10.490
.907
.852
.906
I am worried about the procedure.
10.40
12.651
.864
.773
.924
The procedure is on my mind
continually.
11.02
11.135
.846
.792
.926
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The results of reliability evaluation suggest that 4 items evaluating anxiety can be used as
one-dimensional. The second factor contains only 2 items. The correlation of these items
measuring need for information is .738.
Conclusion
Internal consistency of the APAIS as a one-dimensional tool is very high and the result is the
same for the Anxiety subscale.
Construct validity of the APAIS
To examine the construct aspect of the APAIS validity we firstly correlated the sum score of
the APAIS and both subscales scores with the scores of the STAI, the HADS and the
Anxiety Level-12. Results of Pearson correlations for the whole sample and for the
departments can be seen in the Table 9.
Table 9 Correlations of the APAIS and the STAI, the HADS, the Anxiety Level-12
APAIS
Total
APAIS
Anxiety
APAIS
Need for Information
STAI
Total sample (n=60)
.627***
.662***
.349**
Clinic of Trauma Surgery and
Orthopaedics (n=30)
.835***
.855***
.452*
Surgical Clinic (n=30)
.637***
.702***
.285 ns
HADS
Total sample (n=60)
.747***
.783***
.427***
Clinic of Trauma Surgery and
Orthopaedics (n=30)
.858***
.868***
.486**
Surgical Clinic (n=30)
.593**
.682***
.201 ns
Anxiety
Level-12
Total sample (n=60)
.756***
.783***
.454***
Clinic of Trauma Surgery and
Orthopaedics (n=30)
.892***
.901***
.509**
Surgical Clinic (n=30)
.653***
.716***
.300 ns
APAIS
Total
Total sample (n=60)
.962***
.773***
Clinic of Trauma Surgery and
Orthopaedics (n=30)
.939***
.714***
Surgical Clinic (n=30)
.958***
.769***
Legend: ns - p>0.05, * p≤0.05, ** p≤0.01, *** p≤0.001
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The APAIS Anxiety subscale correlated significantly with all the anxiety scores (the STAI,
the HADS, the Anxiety Level-12) in the whole sample and in both patient subgroups. So did
the APAIS sum score. The only non-significant correlations were found when correlating
Need for Information subscale with anxiety scores in patients at the surgical clinic.
In the next step we verified expected differences based on sex, type of surgery (emergency
or planned) and previous experience with surgery. Firstly we applied ANOVA to examine if
there are any differences in the APAIS scores between two subgroups of patients.
Table 10 Differences in the APAIS scores in patients at two departments
Clinic of Trauma
Surgery and
Orthopaedics
(n=30)
Surgical Clinic
(n=30)
Total (n=60)
F
p
η2
APAIS Total
M
19.93
26.00
22.97
22.238
≤ 0.001
.277
SD
5.46
4.46
5.81
APAIS Anxiety
M
12.27
16.93
14.60
22.038
≤ 0.001
.275
SD
4.23
3.42
4.48
APAIS Need
for Information
M
7.67
9.07
8.37
8.857
≤ 0.05
.132
SD
2.07
1.53
1.94
Patients hospitalized at the Clinic of Trauma Surgery and Orthopaedics and the Surgical
Clinic were found to differ in the APAIS sum score and both subscales scores. All the scores
were significantly higher in patients at the Surgical Clinic. Because of a relatively small
sample size, the following analyses refer to the whole sample.
Differences between male and female patients are presented in the Table 11. Women
reported both higher anxiety and higher need for information than men, resulting in the 6-
point difference in the sum score.
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Table 11 Differences in the APAIS scores in men and women
Men (n=15)
Women (n=45)
Total (n=60)
F
p
η2
APAIS Total
M
18.47
24.47
22.97
14.802
≤ 0.001
.203
SD
5.69
5.07
5.81
APAIS Anxiety
M
11.27
15.71
14.60
13.368
≤ 0.001
.187
SD
4.43
3.96
4.48
APAIS Need for
Information
M
7.20
8.76
8.37
8.109
≤ 0.05
.123
SD
2.27
1.67
1.94
Verification of potential differences caused by the type of surgery planned or emergency
showed only one significant result. Need for information score was slightly higher in patients
who were waiting for the surgery planned in advance; in emergency patients the need for
information was lower.
Table 12 Differences in the APAIS scores in patients waiting for the planned surgery or
emergency surgery
Planned (n=46)
Emergency
(n=14)
Total (n=60)
F
p
η2
APAIS Total
M
23.26
22.00
22.97
.501
.482
.009
SD
6.08
4.88
5.81
APAIS Anxiety
M
14.61
14.57
14.60
.001
.979
.000
SD
4.80
3.37
4.48
APAIS Need for
Information
M
8.65
7.43
8.37
4.528
≤ 0.05
.072
SD
1.84
2.03
1.94
Finally we present the results of differences based on previous experience with surgery
(Table 13). The APAIS seems to differentiate between these patients in our sample sum
and anxiety scores were higher in patients with no previous experience with surgery.
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Table 13 Differences in the APAIS scores in patients with or without previous experience
with surgery
Previous
experience
(n=9)
No previous
experience
(n=51)
Total (n=60)
F
p
η2
APAIS Total
M
17.67
23.90
22.97
10.180
≤ 0.01
.149
SD
5.87
5.33
5.81
APAIS Anxiety
M
10.44
15.33
14.60
10.567
≤ 0.01
.154
SD
4.03
4.18
4.48
APAIS Need for
Information
M
7.22
8.57
8.37
3.866
.054
.062
SD
2.44
1.79
1.94
Discussion
The aim of the study was to provide evidence of the APAIS psychometric quality and to
contribute to the process of the APAIS validations in various countries, e.g. Dutch
(Moerman et al., 1996), Germany (Berth et al., 2007), Japan (Nishimori et al., 2002) and
France (Maurice-Szamburski et al., 2013). What our study adds, is validation of the APAIS
not only against anxiety self-report tools, but also against anxiety rating by the nurse. We
examined three domains of validity and reliability factor validity, internal consistency and
construct validity. In the next section, we discuss the results in the context of literature on the
issue of preoperative anxiety assessment, information-related behaviour in threatening
situations and several published APAIS validation studies. The structure of discussion
matches the structure of result presentation.
Factor structure of the APAIS
In our sample the two-factor solution (anxiety 4 items and need for information 2 items)
was identified explaining 86% of total variance which is in accordance with Berth et al.
(2007) and Nishimori et al. (2002). With the same amount of variance explained, Maurice-
Szamburski et al. (2013) found three-dimensional structure as the original scale (Moerman et
al., 1996): anxiety about anaesthesia (2 items), anxiety about surgery (2 items), and the
desire for information (2 items). This domain remains to be examined in a larger sample.
46
Reliability of the APAIS
The analysis of reliability revealed high reliability of the scales despite their brevity, which
allows for the use of sum scores of the scales.
Construct validity of the APAIS
Both the APAIS Anxiety subscale score and the APAIS sum score correlated significantly
with the scores of the STAI, the HADS and the Anxiety Level-12 in the whole sample and in
both patient subgroups suggesting good construct validity. Since it is rather rare to confirm
a relationship of self-report and rating scores, we can consider presented results satisfying.
In the next step, we identified differences between patients hospitalized at the Clinic of
Trauma Surgery and Orthopaedics and at the Surgical Clinic. They were found to differ in
the APAIS sum score and both subscales scores, with all the scores significantly higher in
patients at the Surgical Clinic. This finding can be explained by distribution of male and
female patients at the Surgical Clinic only women participated in the study.
Further the procedures focused on the hypotheses based on the results of previous research
about subgroups of patients who tend to report higher preoperative anxiety. The first factor is
related to sex women consistently have higher scores in preoperative anxiety
measurements (Moerman et al., 1996; Kindler et al., 2000; Nishimori et al., 2002; Khan,
Nazir, 2007; Romanik et al., 2009). The results in our sample support this hypothesis
despite uneven distribution of both sexes in the sample, women reported significantly higher
anxiety, a finding that other studies failed to confirm (e.g. Berth et al., 2007).
Another possible predictor of preoperative anxiety is no previous experience with surgery
and anaesthesia or negative experience (Shafer et al., 1996; Kindler et al., 2000). Despite the
low frequency of patients with previous surgeries in the sample, only 9, we found significant
differences in both anxiety and sum scores. Patients with no previous experience with
surgery were more anxious than patients who had experienced surgery. Nishimori et al.
(2007) did not find association between anxiety and previous experience with surgery and
therefore they recommend evaluating emotional valency of patients‘ memories of surgery in
the future research. Minor difference was found in the groups based on the type of surgery
need for information score was slightly higher in patients who were waiting for the surgery
47
planned in advance as compared to emergency patients. This may be caused by longer time
patients with planned surgery have to wait, with more time for potential rumination about the
possible threats related to the procedure.
Finally, research shows that patients who require a lot of information manifest higher levels
of preoperative anxiety (Moerman et al., 1996; Nishimori et al., 2002). In our sample, strong
relationship between anxiety and need for information was revealed at the Clinic of Trauma
Surgery and Orthopaedics but not at the Surgical Clinic. Given the uneven distribution of
male and female patients, the interpretation remains unclear.
Nevertheless, some limitations should be mentioned. The most serious threat to results
validity is related to the sample size. However, authors of validation in Germany (Berth et
al., 2007) worked with the simmilar size and structure of a sample. Patients in our sample
were mainly older, with no life-threatening conditions. We did not focus on the seriousness
of surgery (minor or major), potential variability related to regional and general anaesthesia
procedures or how patients evaluate their previous experience with surgery. Future research
following our first trial should address these issues.
Conclusion
The Slovak version of the APAIS is valid and reliable. Our results are simmilar to those of
validation studies across various countries, which supports our adaptation of the scale and
offers options for cross-cultural research. The APAIS is a promising instrument, useful
especially for fast screening due to its potential of detecting patients who may be at risk of
preoperative anxiety and who may benefit from tailored preoperative education.
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There is growing empirical evidence that association of coping style and the amount of provided information influence anxiety prior to surgical procedure or threatening medical examination. The aim of the study is to critically evaluate findings concerning the association of monitoring-blunting cognitive coping style, preoperative information and preoperative anxiety. The EBSCO Research Databases, ProQuest Central, ScienceDirect and SCOPUS databases were searched for studies published since 1980. Reference lists of these studies were also searched for additional references. By the search strategy were identified 10 studies that met the inclusion criteria. Analysed studies yielded no consistent results, match of coping style and amount of information was not proved to be an effective anxiety reduction strategy. Methodological limits, suggestions for future research and practical implications are discussed.
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