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Math anxiety, self-efficacy, and ability in British undergraduate nursing students


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Nurses need to be able to make drug calculations competently. In this study, involving 229 second year British nursing students, we explored the influence of mathematics anxiety, self-efficacy, and numerical ability on drug calculation ability and determined which factors would best predict this skill. Strong significant relationships (p < .001) existed between anxiety, self-efficacy, and ability. Students who failed the numerical and/or drug calculation ability tests were more anxious (p < .001) and less confident (p ≤ .002) in performing calculations than those who passed. Numerical ability made the strongest unique contribution in predicting drug calculation ability (beta = 0.50, p < .001) followed by drug calculation self-efficacy (beta = 0.16, p = .04). Early testing is recommended for basic numerical skills. Faculty are advised to refresh students' numerical skills before introducing drug calculations.
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Research in Nursing & Health
, 2012, 35, 178–186
Math Anxiety, Self-Efficacy, and
Ability in British Undergraduate
Nursing Students
Miriam McMullan,
*Ray Jones,
** Susan Lea
Faculty of Health, Education and Society, University of Plymouth, Peninsula Allied Health Centre,
Derriford Road, Plymouth PL4 8AA, UK
Institute of Psychiatry, King’s College London, UK
Accepted 28 December 2011
Abstract: Nurses need to be able to make drug calculations competently.
In this study, involving 229 second year British nursing students, we
explored the influence of mathematics anxiety, self-efficacy, and numerical
ability on drug calculation ability and determined which factors would
best predict this skill. Strong significant relationships (p<.001) existed
between anxiety, self-efficacy, and ability. Students who failed the numerical
and/or drug calculation ability tests were more anxious (p<.001) and less
confident (p.002) in performing calculations than those who passed.
Numerical ability made the strongest unique contribution in predicting
drug calculation ability (beta ¼0.50, p<.001) followed by drug calculation
self-efficacy (beta ¼0.16, p¼.04). Early testing is recommended for basic
numerical skills. Faculty are advised to refresh students’ numerical skills
before introducing drug calculations. ß2012 Wiley Periodicals, Inc. Res Nurs
Health 35:178–186, 2012
Keywords: anxiety; drug-dosage calculations; numerical ability; nursing;
Medication administration remains a traditional,
responsible task nurses perform, which can take
up 40% of their time at work (Armitage &
Knapman, 2003). Patients expect to receive the
right drug, in the right dose, at the right time,
by the right route, but serious failures, including
drug calculation errors do occur. Medication
errors not only adversely affect individual
patients, their families, and health care staff, but
also undermine general public confidence and
can be a significant source of morbidity and
mortality in hospitalized patients (Department
of Health, 2004). The purpose of this study was
to explore the influence of mathematics anxiety,
self-efficacy, and numerical ability in nursing
students on drug calculation ability and to
determine which factors would best predict this
Of the medication errors reported, between
65% and 87% occur during the prescription and
administration stages, with the wrong drug or
the wrong calculated dosage being the two most
common administration errors (Tang, Sheu, Yu,
Wei, & Chen, 2007). LaPointe & Jollis (2003)
found in their 54-month study on cardiology
hospital wards that the cause of 35% of
medication errors was a wrong dose. Kozer
et al. (2004) observed that during simulated
Correspondence to Miriam McMullan
**Professor of Health Informatics.
Published online 19 January 2012 in Wiley Online Library
( DOI: 10.1002/nur.21460
ß2012 Wiley Periodicals, Inc.
resuscitation tasks, 10-fold errors in dosing
occurred on 3% of occasions and that in 7% of
the cases the injected concentration differed
from the expected concentration by >50%.
Garnerin, Pellet-Meier, Chopard, Perneger, and
Bonnabry (2007) in a small study found that
when 30 nurses and 28 anesthetists were
observed preparing an injection, 24% of the
nurses made arithmetical calculation errors
compared to 9% of the anesthetists. In a larger
study, Parshuram et al. (2008) found that of the
464 intravenous infusions prepared for use in
neonates, 161 (35%) were made up in the wrong
concentration. As these types of drug calculation
errors can have serious consequences, it is
essential that this critical skill be accurately
developed and that personal factors that could
potentially influence this development, such as
having poor numerical skills, being anxious in
performing numerical tasks, or having low levels
of confidence (self-efficacy) in performing
numerical and drug calculations, be identified
as early as possible in order for them to be
Many educators assume that students entering
higher education are numerically competent and
be able to carry out basic numerical calculations,
such as addition, subtraction, multiplication,
and division with whole numbers, fractions,
decimals, ratios, percentages, and conversions
(Jukes & Gilchrist, 2006). Anecdotally, an often
unstated assumption is that nurses should
achieve 100% marks in simple numeracy, but
the mean score of 868 undergraduate American
nursing students was 75% (Brown, 2002),
and 64% of 37 British nursing students were
unable to achieve 70% (Jukes & Gilchrist,
2006). A growing deficit among university
entrants in basic numerical dexterity, apprecia-
tion of number, and basic algebraic reasoning
has been reported for nursing students,
psychology students (Mulhern & Wylie, 2004),
bioscience undergraduates (Tariq, 2004),
and medical students (Conroy & Carroll,
Poor mathematics performance can be the
result of interplay among many factors, one
of them being mathematics (math) anxiety,
which is reputed to interfere with mathematics
cognition (Sheffield & Hunt, 2007). Richardson
and Suinn (1972, p. 551) defined mathematics
anxiety as: ‘‘feelings of tension and anxiety that
interfere with the manipulation of numbers
and the solving of mathematical problems in a
wide variety of ordinary life and academic
situations.’’ Glaister (2007), in her study of
97 second year nursing students, reported a
prevalence of math anxiety of 20%. More
recently, Bull (2009) in her study of 62 first
year nursing students, reported 45% math
anxiety prevalence. Pedagogic researchers have
demonstrated consistently that higher math
anxiety levels are associated with lower per-
formance levels (e.g., Sheffield & Hunt,
2007). In Australia, Glaister (2007) found that
students with greater negative attitudes towards
mathematics performed less well in drug
calculations tests than those reporting less
In addition to math anxiety, students’ drug
calculations ability might also be influenced by
their mathematics and drug calculations self-
efficacy levels. Self-efficacy, according to
Bandura (1977), is the belief that one is capable
of successfully performing a task. Bandura
eventually embedded self-efficacy in his more
general social cognitive theory (Bandura, 1986),
which became the overarching theoretical
framework of the self-efficacy construct. In his
revised framework, although anxiety and self-
efficacy are inversely related, a person’s self-
efficacy level is not as much influenced by
the presence of the anxiety response as by the
interpretation of the presence of this response
by the individual. For example, ‘‘having
butterflies in the stomach’’ will be interpreted
by persons with low self-efficacy as a sign of
their own inability, decreasing their self-efficacy
further, and a person with high self-efficacy will
interpret such a sign as normal and unrelated to
his or her ability.
Pedagogical researchers have demonstrated
the important role that math self-efficacy plays
in predicting math performance (Stevens,
Olivarez, Lan, & Tallent-Runnels, 2004) and
how performance prediction will be greatly
enhanced if efficacy assessments are tailored to
the performance task (Pajares, 1997). Maag
(2004) studied 96 undergraduate nursing students
to assess the effectiveness of an interactive
multimedia learning tool on the students’ math
self-efficacy and math performance scores.
No significant change in math performance
or math self-efficacy scores was found, but
post-intervention there was a moderate correla-
tion between the students’ mathematics test
scores and their self-efficacy results (r¼.28;
In summary, although many nursing students
find it difficult to accurately perform drug
calculations, the reasons for this difficulty are
unclear. They may include poor basic numerical
Research in Nursing & Health
skills, anxiety towards learning mathematics,
and/or a lack of confidence (Mayo & Duncan,
2004). Any factors that could potentially
influence the development of students’ drug
calculation ability need to be identified and
addressed as early as possible. For early
identification and support of those students who
might struggle with drug calculations, it is
particularly important to determine if, and how
strongly, participants’ drug calculation ability
scores could be predicted by individual factors
of anxiety, self-efficacy, and numerical ability.
The aim of this study was therefore to explore
personal factors that could potentially influence
the development of drug calculation ability,
including math anxiety, math and drug calcula-
tion self-efficacy, and numerical ability, and to
determine which, if any, of these factors would
be the best predictor(s) of drug calculation
ability. The research questions were the
following: What are the relationships between
math anxiety, math and drug calculation self-
efficacy, numerical ability, and drug calculation
ability? Are there differences in the anxiety
and self-efficacy levels between students who
pass and those who fail numerical and/or drug
calculation ability tests (DCAT)? Which factors
best predict drug calculation ability?
A cross-sectional research design was used with
a convenience sample of all the second year
undergraduate nursing students (n¼229)
attending a British University. A third of the
nursing students were 24 years or younger,
with 10% of the students aged over 45. Most
participants (93%) were female. Ethnicity
information was not obtained. The study was
approved by the university research ethics
committee. None of the participants were
known to the researchers. Participants were
given information regarding the study in a letter
a few weeks before the study started. The
letter provided contact details in case further
information was required and in case participants
wanted to obtain the results of the study.
Participants were assured their data would
remain confidential. The tests were only used
for the study and did not form part of any
formal assessment. Return of the tests implied
consent and was not compulsory.
Mathematics Anxiety Scale (MAS). Mathe-
matics anxiety has been assessed with various
instruments. Most prominent is the 98-item
Mathematics Anxiety Rating Scale (MARS)
developed by Richardson and Suinn (1972).
However, the length of that instrument has been
a barrier to its use. Therefore, an adaptation by
Betz (1978) of the anxiety subscale of the
Fennema–Sherman Mathematics Attitudes Scales
(Fennema & Sherman, 1976), the MAS, was
used to assess math anxiety. This scale consists
of 10 items using a 5-point Likert-type scale
(1 ¼strongly disagree,5¼strongly agree),
with the first five items positively worded and
the last five negatively worded. For scoring the
positively worded items were reversed so that a
high score indicates high anxiety. Scores could
thus range from 10 (low level of math anxiety)
to 50 (high level of math anxiety). The scores
were converted into percentages for analysis
and could range from 0% to 100%. The
MAS had been found to have strong internal
consistency and stability. Correlations of 0.70
have been reported between the MAS and the
full scale 98-item MARS (Cooper & Robinson,
1991) indicating concurrent validity of the
scale. Hackett & Betz (1989) reported Cronbach
alpha values ranging from 0.86 to 0.90. Dew,
Galassi, and Galassi (1984) reported a Cronbach
alpha of 0.72 and a 2 week test–retest reliability
of 0.87 on a sample of 769 undergraduates,
providing some evidence that MAS scores are
stable over a short time. The Cronbach alpha
value for this study’s sample was 0.94 with 228
(99.6%) students completing the MAS.
Numerical ability test (NAT). This test was
developed from an Australian validated literacy
and numeracy test for Certificate 4 in nursing.
This test is a prerequisite entrance test for
Trainee Enrolled Nurses applying for jobs in
Australian New South Wales Health facilities.
Before use, the test had been validated by UK
nursing academics to be at the appropriate
difficulty level for British students. The test
contains 15 questions covering key calculation
skills (such as multiplication, addition, fractions,
subtraction, percentages, multiplication, decimals,
and conversions). The test’s final score can
range from 0 to 22. The scores were converted
into percentages for analysis, and a grade
of 60% was required to pass. All students
(n¼229) returned the test.
Mathematics Self-Efficacy Scale (MSES).
Two widely used scales that addressed the
Research in Nursing & Health
concept of self-confidence in mathematics are
the confidence subscale of the Fennema–
Sherman Mathematics Attitudes Scales (MAS,
Fennema & Sherman, 1976) and the MSES
developed by Betz and Hackett in 1983. The
confidence subscale of the MAS, however,
tends to measure how confident students feel in
learning mathematics (generalized confidence);
the MSES assesses how confident individuals
are in doing mathematics. Therefore, to determine
how confident students felt in completing
mathematics related tasks used in everyday life,
the task subscale of the MSES was used. To
complete the 18 items scale, individuals are
asked for each item to indicate on a 10-point
scale ranging from ‘‘no confidence at all’ (1)
to ‘complete confidence’’ (10) their confidence
in their ability to successfully perform the
item’s task. The final score for the MSES
task subscale can range from 18 to 180. The
scores were converted into percentages for
analysis. Betz and Hackett reported a Cronbach
reliability coefficient alpha of 0.92 for the task
subscale and a correlation of 0.66 between
the MSES and the confidence subscale of the
Fennema–Sherman MAS (Fennema & Sherman,
1976). In Nielsen and Moore’s (2003) study
with 302 Australian high school students,
significant correlations between MSES scores,
past mathematics grades, and Marsh’s Self-
Description Questionnaire III (Math) demonstrated
convergent validity of scores for the MSES.
Significant correlations between MSES scores
and students’ desired mathematics grades
indicated concurrent validity of the MSES
measures. Hackett and O’Halloran (1985, cited
in Hackett & Betz, 1989) reported that the
test–retest reliability of the MSES over a
2-week interval for the tasks subscale was 0.79.
For the sample in this study the Cronbach alpha
coefficient was 0.95 with 226 students (98.7%)
returning the test.
Drug Calculations Self-Efficacy Scale
(DCSES). The DCSES, devised by the princi-
pal author, consists of six items covering the
principal areas of medication calculations,
(i.e., calculating dosages for liquid oral medica-
tions, solid medications, injections, percentage
solutions, and calculating infusion rates and
drip rates). To complete the scale individuals
are asked for each of the six items to indicate
on a 10-point continuum scale ranging
from ‘‘no confidence at all’ (1) to ‘extremely
confident’ (10) their confidence in their ability
to successfully perform the item’s task. The
final score can range from 0 to 60. The scores
were converted into percentages for analysis.
The scale was demonstrated to have good
reliability with a Cronbach alpha coefficient
larger than 0.90 in a pilot study with 22 first
year students. Significant correlations of 0.80
between the DCSES and the MSES indicated
the scale has concurrent validity. The Cronbach
alpha coefficient for this study’s sample was
0.93 with 225 students (98.2%) returning the
Drug Calculation Ability Test (DCAT). The
DCAT, devised by the principal author, contains
20 questions covering the principal areas of
medication calculations, (i.e., calculating dosages
for liquid oral medications, solid medications,
injections, percentage solutions, and calculating
infusion rates and drip rates). Calculators may
not be used during the test. The scores were
converted into percentages for analysis. To
independently check for face validity, the test
was sent before use to three nursing academics
with expertise in medication calculations.
Feedback and corrections received (e.g., specific
drug dosages) were incorporated into the test.
All students (n¼229) returned the test.
Data Collection Procedure
The participants were recruited halfway through
their second year of undergraduate school
following a module on drug calculations.
Participation was voluntary. The tests were
administered to students in large classes by
the researchers. That the DCAT was at the
difficulty level appropriate for these students was
confirmed by the module faculty. Participants
were allowed to use pen and paper when
performing calculations but not calculators
as these could act as a substitute for the
participants’ arithmetical skills and knowledge
(Nursing and Midwifery Council, 2002).
Data Analysis
Descriptive and inferential statistical analyses
were applied to the quantitative data using
SPSS version 15.0 (SPSS Inc., Chicago, IL).
Pearson product-moment analysis was used to
explore inter-relationships between variables,
and standard multiple regression was applied to
determine statistically significant explanatory
variables. The independent samples t-test was
used to determine differences between groups.
Research in Nursing & Health
considerable variation among participants
(Table 1). For example, scores for math anxiety
ranged from the minimum to the maximum
With 60% being the pass mark, 126 (55%) of
the participants failed the NAT, and 210 (92%)
of the participants failed the DCAT. As can be
seen in Table 2 low levels of math anxiety
(score 0–24%) were demonstrated by 10%
of the students, 70% demonstrated medium
levels of math anxiety (score 25–74%); 20%
demonstrated high levels of math anxiety
There were significant correlations between
all the variables (Table 3) with the strongest
being between math and drug calculation
self-efficacy, math anxiety and self-efficacy,
numerical and drug calculation abilities, and
math anxiety and drug calculation ability.
Cross-tabulations results indicated that 93%
of the students who failed the numeracy test
and 83% of the students who failed the drug
calculation test demonstrated signs of math
anxiety (score25%). In comparison, 63% of
the students who passed the numeracy test
and 32% of the students who passed the drug
calculation test demonstrated math anxiety
Independent samples t-tests (Table 4)
demonstrated that students who failed the
numeracy test were significantly more anxious
(t[216] ¼7.04, p<.001) and less confident
(t[214] ¼5.77, p<.001) in performing
numerical calculations and less confident in
performing drug calculations (t[213] ¼3.42,
p¼.001) than those who passed. In addition,
independent samples t-tests demonstrated that
students who failed the drug calculation test
were significantly more anxious (t[226] ¼4.43,
p<.001) and less confident (t[224] ¼3.18,
p¼.002) in performing numerical calculations
and less confident in performing drug
calculations (t[223] ¼2.48, p¼.014) than
those who passed the test.
Prediction of Drug Calculation Ability
Before carrying out multiple regression analysis,
the linearity between dependent and independent
variables, normality, homoscedasticity, and
multicollinearity were checked. In the multiple
regression analysis, any missing cases were
excluded pairwise. Results of the multiple
regression, which included as independent
variables numerical ability, math anxiety, and
math and drug calculation self-efficacy, indicated
a good fit (R
¼36.5%) and the overall
relationship was significant (F[4,217] ¼31.2,
p<.001). Numerical ability (beta ¼0.500,
p<.001) made the strongest unique contribu-
tion, when controlling for the other variables,
followed by drug calculation self-efficacy
(beta ¼0.162, p¼.036). Math anxiety and
math self-efficacy were non-significant. When
the non-significant variables of math anxiety
and self-efficacy were removed, the model
remained a good fit (R
¼36.3%) and the
overall relationship was significant (F[2,222] ¼
63.3, p<.001). Numerical ability (beta ¼.52,
p<.001) made the strongest unique contribu-
tion, when controlled for other variables,
followed by drug calculation self-efficacy
(beta ¼0.18, p<.001).
The findings demonstrated a strongly significant
positive relationship between participants’
Table 1. Descriptive Statistics of the Study Variables
Variable nMin % Max % Mean (SD) %
Math anxiety 228 0.0 100.0 58.6 (22.9)
Math self-efficacy 226 2.8 94.4 54.4 (19.4)
Drug calculations self-efficacy 225 10.0 93.3 45.6 (18.8)
Numerical ability 229 2.3 100.0 54.8 (24.7)
Drug calculation ability 229 0.0 85.0 36.2 (15.1)
Table 2. Math Anxiety Scores (n¼228)
Math anxiety scores n%
10%–24% 23 10
25%–74% 160 70
75% 45 20
Research in Nursing & Health
numerical and drug calculation ability levels.
This result, together with the regression analysis
result indicating numerical ability to be the
main predictor of drug calculation ability,
demonstrate empirically the importance of
basic numerical skills for performing drug
calculations. Both the numerical and drug
calculation abilities of the participants were
found to be poor. The reasons for this can
only be speculated upon, but could include
dependence on calculators and inadequate
previous mathematical education (McMullan,
Jones, & Lea, 2010). However, no matter the
reason, the results suggest that any mathematical
deficits need to be identified early on (ideally at
admission) and corrected as soon as possible.
There was not only a significant positive
relationship between students’ math self-efficacy
and math performance, but also significant
positive relationships between math self-efficacy,
drug calculation self-efficacy, and drug calcula-
tion performance. This confirmed recent results
of Andrew, Salamonson, and Halcomb (2009),
who in a study of 112 second year students
found that those who had high math self-efficacy
scores performed significantly better in a drug
calculation exam than those who had low
math self-efficacy scores (t¼2.65, p¼.009).
Together these findings empirically support
Bandura’s (1986) self-efficacy theory, which
suggests that self-efficacy beliefs influence
performance, mainly through their effect on
effort, persistence, and perseverance.
An important way to improve a person’s self-
efficacy is by providing positive encouragement
and constructive feedback. There is consistent
evidence demonstrating that evaluative feedback
(either ability or effort feedback) during
mathematics practice increases mathematics
self-efficacy and achievement (Schunk &
Hanson, 1989). However, how the feedback is
perceived depends very much on the credibility
and competence of the person who provides it
and whether the encouragement and feedback
given is realistic and sincere, otherwise it can
negatively affect self-efficacy beliefs (Bandura,
1986, 1997).
Regarding the effect of math anxiety, partici-
pants in this study who failed the numerical
and/or drug calculation tests were significantly
more anxious in performing calculations than
those who scored higher. In addition, significant
negative relationships were found between
participants’ levels of math anxiety and their
levels of self-efficacy and ability in perform-
ing numerical and drug calculations. Similar
results had been found by Bull (2009), who
demonstrated the existence of a significant
Table 3. Bivariate Correlations
Drug calculation
Drug calculation
Math anxiety
Math self-efficacy .63
Drug calculation self-efficacy .49
Drug calculation ability .52
Numerical ability .39
p<.001 (2-tailed).
Table 4. Math Anxiety, Math, and Drug Calculations Self-Efficacy Mean (SD) Scores for Students Who
Failed (Scores of <60%) and Passed (Scores 60%) the Numerical and DCATs
Numerical ability test scores Drug calculation ability test scores
<60% 60% t-test 60% 60% t-test
Mean (SD) Mean (SD) pMean (SD) Mean (SD) p
Math anxiety % 68.0 (17.2) 48.2 (24.0) <.001 60.6 (21.6) 37.2 (26.4) <.001
Math self-efficacy % 47.9 (19.0) 62.2 (17.3) <.001 53.5 (18.9) 68.0 (20.6) .002
Drug calculations
self-efficacy %
41.2 (18.5) 49.7 (17.8) <.001 44.6 (18.4) 55.6 (20.3) .014
Research in Nursing & Health
negative correlation between students’ math
anxiety levels and their math test scores
(r¼.34, p¼.01). This finding of an inverse
relationship between anxiety and self-efficacy
supports Bandura’s (1986) social cognitive
theory in which he argued that increased
anxiety would lead to reduced self-efficacy and
vice versa. This study’s results, however, not
only demonstrated the presence of a negative
association between math anxiety and math
performance, but also between math anxiety
and drug calculation ability. This negative
association is probably indirect, in that math
anxiety affects numerical ability and vice versa,
which in turn will have an effect on drug
calculation ability.
The mechanism through which the students’
high math anxiety potentially influences their
math and drug calculation performances could
be indirectly through avoidance. This indirect
effect has been described by Preis & Biggs
(2001) as the Math Anxiety Cycle. The cycle
starts with the student having developed math
anxiety, possibly due to negative experiences
with math in the past. As a result of this anxiety
the student will avoid math situations or put in
little effort. This will subsequently lead to poor
math performance causing further increased
anxiety, reduced confidence, and avoidance. The
cycle can repeat itself so often that the math
anxious person will become convinced of his
or her inability to do math and, if the cycle is
not broken, this can eventually turn into a
permanent block.
Why certain students suffer from math
anxiety is not always clear, but the beginnings
of math anxiety can often be traced back to
negative classroom experiences and the manner
in which mathematics was taught at school,
such as the presence of gender bias, insensitive/
uncaring teachers, and embarrassment and
humiliation in front of peers (Jackson &
Leffingwell, 1999). According to Arem (1993),
these negative experiences with math in the
formative years can haunt students even into
their adulthood and can become a block to
their subsequent learning. These students have
lost confidence in their ability to perform
calculations resulting in increased anxiety
when they are asked to do so. It is therefore
important that, for students who suffer from
math anxiety, this anxiety is identified and
addressed as soon as possible, as the anxiety
can prevent them from reaching their true
potential in obtaining mathematical and drug
calculation proficiency.
To lessen math anxiety, a positive and
supportive learning environment is needed
(Uusimaki & Nason, 2004). Teaching, instead
of being didactic should be more student
directed (Farrell, 2006). According to Brewer
& Daane (2002), cooperative groups enable
students to exchange and clarify ideas, to ask
questions, and to provide explanations. They
found that these cooperating students had
greater understanding of mathematics and
experienced more success than those in
traditional classrooms. Murray, Ma, and Mazur
(2009) argued that as students have different
learning styles, instruction must be caring and
flexible enough to meet the needs of all the
students, and be able to address the frustration
that often leads to math anxiety.
While the results highlight some important
and interesting issues for nurse education, the
study was carried out in only one UK higher
education institute and therefore caution should
be taken in generalizing the findings. Although
valuable information was obtained from the
scales, these data were self-reported.
The results of this study demonstrate numerical
ability, closely followed by math anxiety, to be
the main personal factors potentially influencing
students’ drug calculation ability development.
To improve drug calculation ability, early
identification of individuals who have problems
with numeracy is essential. This identification
testing can be done either at the time of the
admission interview or at the beginning of
the program. Subsequently, to improve their
numerical skills, these students can be targeted
by a range of remedial approaches such as
lectures, study groups, workbooks, and computer
assisted instruction (Jukes & Gilchrist, 2006). In
the end, to reduce math anxiety and improve
numerical ability, the best remedy is a caring
teacher in a supportive environment using
multiple teaching strategies that address the
needs of all students.
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... Notice that Richardson and Suinn (1972) included this aspect in their math anxiety definition (see above), which is used as reference in many math anxiety studies (e.g., Tomasetto et al., 2020), and that math anxiety can be experienced in everyday settings, for example, when reading a cash register receipt after a purchase or when totaling up a dinner bill that you think overcharged you (e.g., Ashcraft & Moore, 2009). Moreover, the negative impact of math anxiety is not only found in academic tasks but also in other daily life tasks as drug calculations for nursery staff (McMullan et al., 2012), medical risks interpretation (Rolison et al., 2016(Rolison et al., , 2020 or making financial decisions (McKenna & Nickols, 1988). ...
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Background: This study developed the Brief Math Anxiety Scale (BMAS), a brief version of the Shortened Math Anxiety Rating Scale (sMARS), maintaining its original three-factor structure, by applying item response theory. Method: The sMARS was administered to 1,349 undergraduates, along with other questionnaires to measure their math ability, trait and test anxieties, and attitudes toward mathematics. Results: Results showed that the original scale could be reduced to nine items (three for each subscale). We provided evidence of good psychometric properties: strong internal consistency, adequate 7-week test-retest reliability, and good convergent/discriminant validity. Conclusions: In conclusion, the BMAS provides valid interpretations and reliable scores for assessing math anxiety in university students, and is especially useful in situations with time constraints where the longer form is impractical.
... Additionally, failing to address maths anxiety in the classroom could lead to maths anxiety in the workplace and everyday applications. For example, research shows that maths anxiety contributes to substandard drug calculation among nurses (McMullan et al., 2012) and difficulty in financial planning (McKenna & Nickols, 1988). Maths teachers and parents could also pass their maths anxiety to their Teachers and Curriculum, Volume 23, Issue 1, Special Issue: Ngā Timatanga Hou: Fresh Perspectives on Education, 2023 students and children; thus, maths anxiety should be identified and addressed as early as possible in a person's academic life (Asanjarani & Zarebahramabadi, 2021). ...
The purpose of this review was to analyse empirical studies related to reducing mathematics anxiety in the classroom. A scoping process was used to locate literature, and a thematic method was used to analyse and group the data obtained from the studies. A total of 14 articles published between 2014 and 2022, mostly using mixed-methods approaches, were analysed. The data indicated that mindfulness strategies, sustained exposure and support, and addressing affective factors, such as distractions, negative emotions, and motivation, has been shown to reduce mathematics anxiety levels of students. Possible implications for reducing maths anxiety in the classroom and opportunities for further empirical research are presented.
... Azokról az emberekről, akik félelmet és aggodalmat tapasztalnak, amikor szembesülnek a matematikai feladatokkal, azt mondják, hogy szoronganak a matematika miatt (Richardson & Suinn, 1972), és ez a szorongás előfordul akkor is, amikor hétköznapi szituációkban találkoznak a matematikával, például a borravalót számolják ki egy étt eremben, vagy arról döntenek, hogy megfelelően kapták-e a viszszajárót az élelmiszerboltban (McKenna & Nickols, 1988;Maloney & Beilock, 2012;McMullan et al., 2012). ...
Kutatásunkban óvodapedagógus és tanító szakos hallgatók matematikai szorongását vizsgáljuk. 114 hallgató matematikai szorongásának szintjét első féléves tanulmányaik elején és végén mértük kérdőíves módszerrel. Eredményeink alapján elmondható, hogy hallgatóink szorongásának szintje rövid idő alatt is szignifikáns mértékben tud csökkenni és erősödni is. Fontos, hogy képzésünk során az erősen szorongó hallgatók szintjének csökkentésén tudatosan dolgozzanak az oktatók, miközben a kevéssé, vagy közepesen szorongók motivációját fenntartják, illetve erősítik.
... Furthermore, the impact of math anxiety is not limited to students' math performance in academic settings; many adults experience math anxiety during everyday tasks like reading receipts (Maloney & Beilock, 2012). These daily experiences of math anxiety are negatively related to adults' self-efficacy and performance in occupations such as nursing and elementary education (Beilock et al., 2010;McMullan et al., 2012;Swars et al., 2006). ...
Math achievement is one of the strongest predictors of academic success and career attainment. While research has focused on cognitive factors that relate to math achievement, a growing body of literature suggests that affective factors like math anxiety also relate to math achievement. The field of math anxiety has expanded to recognize that not only children's but also parents' math anxiety is related to math performance. Yet, specific mechanisms through which parents' math anxiety relates to children's math performance are not well explicated. In this article, we synthesize research on the relation between parents' math anxiety and children's math achievement, and then propose a comprehensive model (the Parent and Child Math Anxiety Network model) to demonstrate the likely pathways through which parents' math anxiety may affect children's math achievement.
... For decades, there has been a consistent problem with poor performance of nurses taking numeracy tests; to some extent irrespective of accumulated clinical experience (McMullan, Jones & Lea, 2010;Dilles et al. 2011;Arkell & Rutter, 2012). For student nurses, anxiety is an important factor influencing efficacy with drug calculations (McMullan, Jones, & Lea, 2012). Where previously attained qualifications in mathematics provide the strongest nonaffective indicator for success, 'maths anxiety' is the strongest affective predictor for numeracy performance among student nurses (Thompson et al., 2015). ...
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The nursing associate is a new role in England, creating a bridge between unqualified health care assistants and registered nurses. Health Education England (HEE) and the Nursing and Midwifery Council (NMC) were instrumental in designing a national curriculum for this new qualification (HEE, 2017). Pilot schemes were quickly set up, including the launch of the University of Gloucestershire's 2-year Foundation Degree Nursing Associate programme in April 2017. My work supporting Trainee Nursing Associates (TNAs) to meet the new NMC requirements has led to reflection upon issues of educational consistency and, in particular, an exploration of the evidence base for 100% applied numeracy standards. This paper sets out discussion points around consistency and validity that are broadly applicable to nurse education across the U.K.
... Math anxiety (MA) can be described as "feelings of tension and anxiety that interfere with the manipulation of numbers and the solving of mathematical problems in a wide variety of ordinary life and academic situations" (Richardson & Suinn, 1972, p. 551). MA is negatively associated with mathematics learning, mathematics performance, and basic numerical abilities (Bursal & Paznokas, 2006;Maloney & Beilock, 2012;McMullan et al., 2012). Individuals with high levels of math anxiety (HMA) have indeed been shown to perform worse than their low math anxious (LMA) peers on a wide variety of numerical tasks, ranging from counting (Maloney et al., 2011) to more complex arithmetic problems (Ashcraft & Faust, 1994). ...
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Math anxiety results in a drop in performance on various math-related tasks, including the symbolic number ordering task in which participants decide whether a triplet of digits is presented in order (e.g. 3-5-7) or not (e.g. 3-7-5). We investigated whether the strategy repertoire and reaction times during a symbolic ordering task were affected by math anxiety. In study 1, participants performed an untimed symbolic number ordering task and indicated the strategy they used on a trial-by-trial basis. The use of the memory retrieval strategy, based on the immediate recognition of the triplet, decreased with high math anxiety, but disappeared when controlling for general anxiety. In the study 2, participants completed a timed version of the number order task. High math-anxious participants used the decomposition strategy (e.g. 5 is larger than 3 and 7 is larger than 5 to decide whether 3-5-7 is in the correct order) more often, and were slower in responding when both memory- and other decomposition strategies were used. Altogether, both studies demonstrate that high-math anxious participants are not only slower to decide whether a number triplet is in the correct order, but also rely more on procedural strategies.
Conference Paper
Although some researchers have been researching the correlation between self-efficacy and mathematics anxiety, they indicated various correlations. Therefore, we conducted a meta-analysis aimed at determining the strength of the actual correlation between the two variables. Data obtained from primary studies that have been published in journals, proceedings, and dissertations from 2010 to 2021. Data conducted from 46 studies (n=48447), we found a small-to-large, negative and positive, and significant correlation between self-efficacy and mathematics anxiety. Based on analysis using the random-effect model concluded that there was a significant negative relationship between self-efficacy and mathematics anxiety. This showed that the higher self-efficacy, the lower mathematics anxiety. The correlation was in the moderate category (r=-0.164) and confidence interval was on a range -0.228 to -0.101.
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The research aims to determine the difference between secondary school students’ mathematics anxiety with mathematics literacy self-efficacy level and study these connections. The relational screening model in the research population comprises 32 secondary schools in the 2020-2021 academic years in Esenyurt province, Istanbul. Research samplings comprise 1682 students that are chosen with the stratified sampling method from nine different secondary schools in Esenyurt province. Data was gathered by the ‘’Secondary School Mathematics Literacy Self-Efficiency Scale’’ and ‘‘Mathematics Anxiety-Apprehension Survey’’. For data analysis, descriptive statistics, Sperman Correlation Analysis and statistical techniques are used. As a result of the analysis, secondary school students’ mathematics anxiety is higher than average, and their mathematics literacy self-efficacy is also significantly higher. After the examination of the relationship between the scales, it was determined that there is a positive relationship between mathematics anxiety and mathematics literacy self-efficacy.
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Presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the proposed model, expectations of personal efficacy are derived from 4 principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. Factors influencing the cognitive processing of efficacy information arise from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. (21/2 p ref)
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Maths anxiety has been the focus of much psychological and educational research in the past few years. In this article, we review some of this research evidence and describe some of the work we have completed. In particular, we will describe what maths anxiety is and how it has been measured, describe some of the consequences of maths anxiety, and finally describe what can be done to alleviate difficulties associated with math anxiety.
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The authors evaluated self-efficacy and motivational orientation across Hispanic and Caucasian students to predict variables related to mathematics achievement, including mathematics performance and students' plans to take additional mathematics courses. Path models were analyzed for 358 students in Grades 9 and 10 who attended a West Texas high school and for the sample split by ethnicity. The tested models provided adequate goodness of fit to the data, supporting the finding that self-efficacy predicts motivational orientation and mathematics performance. Tests of each model parameter across ethnicity revealed 1 significant difference, suggesting that the relationship between prior mathematics achievement and self-efficacy was stronger for Hispanic students. Findings indicate that similar motivational systems exist to predict mathematics achievement across ethnicity; however, Caucasian students do not place as much emphasis on prior mastery experiences as do Hispanic students, suggesting that other factors are active in influencing their self-efficacy.
This experiment investigated how mastery and coping peer models influenced children's self efficacy and skill. An ethnically mixed sample of 120 fourth-grade children (60 boys, 60 girls, mean age = 9 years, 4 months) observed either one or three same-sex peers learn to solve fraction problems. Mastery models easily grasped fraction operations and verbalized positive achievement beliefs. Coping-emotive models initially experienced difficulties learning and verbalized negative emotive statements, after which they displayed coping behaviors and eventually performed as well as mastery models. Coping-alone models performed in identical fashion to coping-emotive models but never verbalized negative achievement beliefs. Coping-emotive models led to the highest self-efficacy for learning. Mastery and coping-alone subjects perceived the model as competent and themselves as equally competent, whereas coping-emotive subjects viewed themselves as more competent than the model. No differences were obtained due to number of models.
I just don't like math.” How often have students uttered these anxiety-based words? The primary purpose of this research was to investigate the types of instructor behavior that created or exacerbated anxiety. In addition, the authors wanted to determine the grade levels (K—college) in which mathematics anxiety first occurred in these students. In this article, the term instructor includes anyone who teaches at any level, kindergarten through college.
Many associate degree nursing students lack basic computational mathematic ability. When a computational mathematics test was administered to more than 850 associate degree nursing students nationwide, the results were amazingly consistent. The mean student score on the Computational Arithmetic Test was 75%. The findings showed that students were mathematically underprepared, particularly in skills involving fractions, decimals, and percents, the mathematic skills necessary for medication calculation. The author also surveyed associate degree nursing faculty (n = 118) from the same schools of nursing as to how successful they felt their students would be on a computational mathematics test. The average faculty expected student performance was 88%.
This study describes nurse perceptions about medication errors. Findings reveal that there are differences in the perceptions of nurses about the causes and reporting of medication errors. Causes include illegible physician handwriting and distracted, tired, and exhausted nurses. Only 45.6% of the 983 nurses believed that all drug errors are reported, and reasons for not reporting include fear of manager and peer reactions. The study findings can be used in programs designed to promote medication error recognition and reduce or eliminate barriers to reporting.
Background: The Institute of Medicine's report To Err Is Human: Building a Safer Health System recommends pharmacist participation in patient rounds as an immediate approach to reducing medical errors. In the same report and in prior publications, cardiovascular drugs have been commonly associated with severe adverse drug events. Methods: We systematically reviewed the experience of a clinical pharmacist on the cardiology wards between September 1, 1995, and February 18, 2000. We classified medication errors according to the type of error, medications involved, personnel involved, stages of drug administration involved, and time of year most frequently associated with errors. Results: Among 14983 pharmacist interventions, 4768 were related to medication errors, or 24 medication errors per 100 admissions. The most common errors involved the wrong drug (36.0%) or wrong dose (35.3%), and cardiovascular medications were involved in 41.2% of the errors. Prescribers were associated with most of the errors, and the transition from outpatient to inpatient was the most common point in the system for the occurrence of these medication errors. Higher numbers of errors were also identified during the transition period of house staff, and the total number of errors increased during the study period. Conclusions: Through the clinical pharmacist's identification and correction of medication errors, 2 areas of improvement that may reduce medication errors were identified. The first is ensuring accurate knowledge of a patient's outpatient medication regimen. The second involves improving the education and support of new interns during their initial months of training. This work exemplifies the approach recommended by the institute of Medicine to reduce medical errors through systematic analyses rather than ascribing fault to individuals.