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The Brunel Mood Scale Rating in Mental Health for Physically Active and Apparently Healthy Populations

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There is a positive relationship between mood states and mental health. The aim of the present study was to investigate the construct validity and internal consistency of the Brunel Mood Scale (BRUMS) for use with different populations, which are physically active and apparently healthy. Measures were obtained from 1295 male (N = 709, 34 ± 20 years, mean ± SD) and female (N = 576, 43 ± 24 years, mean ± SD) volunteers. Factor analysis was used, verifying that six factors (components) accounted for 62.65% of the total variance of the scale. The Varimax method with Kaiser Normalization for the rotation of the factors for the main components, and it was observed that the 24 scale items loaded on six mood factors (anger, depression, tension, vigor, fatigue, and confusion). Internal consistency was good for all the factors identified. We suggest that the results provide some support for validity of the BRUMS for use with different populations, which are physically active and apparently healthy.
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Health, 2016, 8, 125-132
Published Online January 2016 in SciRes. http://www.scirp.org/journal/health
http://dx.doi.org/10.4236/health.2016.82015
How to cite this paper: Brandt, R., et al. (2016) The Brunel Mood Scale Rating in Mental Health for Physically Active and
Apparently Healthy Populations. Health , 8, 125-132. http://dx.doi.org/10.4236/health.2016.82015
The Brunel Mood Scale Rating in
Mental Health for Physically
Active and Apparently
Healthy Populations
Ricardo Brandt1,2, Dafne Herrero3, Thaís Massetti4, Tânia Brusque Crocetta2,5,
Regiani Guarnieri5, Carlos Bandeira de Mello Monteiro4,5, Maick da Silveira Viana2,
Guilherme Guimarães Bevilacqua2, Luiz Carlos de Abreu5, Alexandro Andrade2
1State University of West Parana, Marechal Cândido Rondon, Brazil
2Laboratory of Sport and Exercise Psychology, Santa Catarina State University, Florianópolis, Brazil
3Faculty Public Health, São Paulo, Brazil
4Post-Graduate Program in Rehabilitation Sciences, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
5Department of Morphology and Physiology, Faculty of Medicine of ABC, Santo André, Brazil
Received 27 August 2015; accepted 25 January 2016; published 28 January 2016
Copyright © 2016 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
There is a positive relationship between mood states and mental health. The aim of the present
study was to investigate the construct validity and internal consistency of the Brunel Mood Scale
(BRUMS) for use with different populations, which are physically active and apparently healthy.
Measures were obtained from 1295 male (N = 709, 34 ± 20 years, mean ± SD) and female (N = 576,
43 ± 24 years, mean ± SD) volunteers. Factor analysis was used, verifying that six factors (compo-
nents) accounted for 62.65% of the total variance of the scale. The Varimax method with Kaiser
Normalization for the rotation of the factors for the main components, and it was observed that
the 24 scale items loaded on six mood factors (anger, depression, tension, vigor, fatigue, and con-
fusion). Internal consistency was good for all the factors identified. We suggest that the results
provide some support for validity of the BRUMS for use with different populations, which are
physically active and apparently healthy.
Keywords
Mental Health, Mood States, Psychometrics, Brunel Mood Scale, BRUMS
R. Brandt et al.
126
1. Introduction
Over the past few decades, there has been a growing body of literature on mental health [1]. However, there is
still a need to develop related research into the association between physical activity and mental health [2], as
problems in this context are a worldwide concern in public health [3], affecting all age groups and accounting
for significant expenditure by governments [4].
There is a positive relationship between mood states and mental health [5] [6]. It is considered that the high
level of vigor associated with lower levels of tension, depression, anger, fatigue and confusion is related to a
better mental health condition [7] [8].
Among the instruments that evaluate moods, the POMS (Profile of Mood States) stands out as one of the most
widely used in different populations [9] [10]. The Brunel Mood Scale (BRUMS), derived from the POMS, the
validation of which in Brazil was performed by Rohlfs et al. [11], was presented as a tool for detection of the
over-training syndrome. In addition, such scales have been used in different populations and contexts in Brazil
[12]-[14] and other countries [15]-[17].
The 24-item BRUMS measures six identifiable mood states (Tension, Depression, Anger, Vigor, Fatigue, and
Confusion) through a self-report inventory. The respondents rating a list of adjectives, on a 5-point Likert scale
from 0 (not at all) to 4 (extremely), on the basis of how they had been feeling in the previous week, or in the
moment of evaluation [12] [18]. The six affective mood states subscales are not diagnostic indicators, but refer
to sub-clinical psychological states (mood states) [19].
This study aims to investigate the construct validity and internal consistency of the BRUMS for different
populations, which are physically active and apparently healthy.
2. Method
This is a descriptive cross-sectional study with non-probability sampling (Sample size calculation was not con-
ducted before sampling). The participants in the study were 1,295 individuals from Santa Catarina state, south of
Brazil, of both sexes, physically active and apparently healthy: 709 (54.7%) men with a mean age of 34 years
(±20) and 586 (45.3%) women, with a mean age of 43 years (±24). Data were collected during 2013 year, from
February to November.
The BRUMS [11] has 24 items arranged into six subscales: anger, confusion, depression, fatigue, tension and
vigor (Table 1), each with four items. The research participant selects, from a numerical rating scale of zero to
four (0 = not at all, 1 = a bit, 2 = moderate, 3 = enough; 4 = extremely), the option they believe best represents
the situation at that time, using questions such as How do you feel now?, How have been feeling in the past
week, including today?, or How have you been feeling?”.
The items on each subscale are:
Anger: annoyed, bitter, angry, bad-tempered;
Confusion: confused, muddled, mixed-up, uncertain;
Depression: depressed, downhearted, unhappy, miserable;
Fatigue: worn out, exhausted, sleepy, tired;
Tension: panicky, anxious, worried, nervous;
Vigor: lively, energetic, active, alert.
Table 1. Dimensions of BRUMS.
DIMENSION
DEFINITION
Tension
State of musculoskeletal tension and worry.
Depression
Emotional state of despondency, sadness, unhappiness.
Anger
State of hostility, for others.
Vigor
State of energy, physical force.
Fatigue
State of tiredness, low energy.
Confusion
State of feeling stunned, instability in emotions.
Reference: Brandt et al. [20].
R. Brandt et al.
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The sum of the responses of each subscale results in a score that ranges from zero to 16. The questionnaire
does not generate an overall score, and each scale should be examined individually, although the constructs are
related.
Survey participants were characterized with respect to other variables, based on the study of Brandt et al. [12],
regarding self perception of sleep quality and self-related health. Self perceived health status and quality of sleep,
composed Likert scale with responses from 0 (very bad) to 4 (excellent) [20]. These questions were used to
compare means of moods, depending on the variables mentioned in the literature, allowing the visualization of
the use of the scale in the research.
All survey participants signed an informed consent and it was approved by the Research Ethics Committee
(44/2011), according to Resolution 196/96 of the National Health Council. A previously trained researcher ad-
ministered the sample individually. The research procedures were explained and the participants asked to point
out if the matter was not clear. For elderly participants, a printed sheet was presented with the response options.
The response time was no longer than six minutes.
Data were tabulated and analyzed using SPSS software version 21.0. The internal consistency of the subscales
was assessed using Cronbachs alpha. The authors of the original instrument [21], found the alpha to be greater
than 0.76, so it is considered an instrument with good internal consistency.
Construct validity was assessed through exploratory factor analysis, which identified the common compo-
nents in a large number of variables. The factor analysis was performed according to the steps proposed by
Dancey and Reidy [22].
We used the principal components method for extracting the factors and considered only those that presented
an eigenvalue of one. For selected factors, a correlation matrix was generated, where relationships between
items and factors were observed through factor loadings. For the purposes of the matrix, the orthogonal rotation
Varimax method was applied, which maximizes high correlations and minimizes casualties, facilitating analysis.
To analyze the results of the mood states, descriptive and inferential statistics (mean and standard deviation)
were used (Kruskal-Wallis and Mann-Whitney).
3. Results
In order to confirm the theoretical factors, factor analysis was used, verifying that the six factors (components)
accounted for 62.65% of the total variance of the scale (Table 2). The KMO (Kaiser-Mayer-Olkin) test (X2 =
0.909, p < 0.001) indicated the proportion of the data variance and their values can be considered suitable, as
well as the Bartlett sphericity test (X2 = 11259.9, p < 0.05), concerning the correlation between the data.
Table 3 shows the correlations (factor loadings) for each item with each factor, respectively. We used the
method of the main components with the Varimax method rotation of the factors, with Kaiser normalization.
The saturation with values was greater than 0.30 and the items appear ordered by factor.
It is observed that the 24 scale items loaded on six mood factors (anger, depression, tension, vigor, fatigue and
confusion), corresponding to the analyses found by Rohlfs et al. [11] in the BRUMS validation to search for
Brazilian athletes and non-athletes.
Table 2. Eigenvalues and explained variance components of the BRUMS.
COMPONENT Eigenvalues initials
Total % Variance % cumulative
1 (Anger) 7.27 30.33 30.33
2 (Depression) 2.62 10.92 41.25
3 (Tension) 1.68 7.03 48.28
4 (Vigor) 1.41 5.91 54.20
5 (Fatigue) 1.13 4.72 58.92
6 (Confusion) 1.01 3.73 62.65
Extraction method: Principal component analysis.
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Table 3. Exploratory factor load for each item in the six factors extracted from the BRUMS.
Component 1 2 3 4 5 6 Cronback Alfa
ITENS Anger Depression Tension Vigor Fatigue Confusion
Annoyed 0.722 0.830
Bitter 0.785 0.826
Angry 0.813 0.831
Bad tempered 0.671 0.830
Depressed 0.648 0.831
Downhearted 0.621 0.831
Unhappy 0.647 0.832
Miserable 0.440 0.832
Panicky 0.388 0.829
Anxious 0.806 0.831
Worried 0.724 0.834
Nervous 0.741 0.831
Lively 0.725 0.851
Energetic 0.773 0.851
Active 0.789 0.851
Alert 0.639 0.852
Worn out 0.776 0.830
Exhausted 0.803 0.829
Sleepy 0.491 0.835
Tired 0.785 0.831
Confused 0.693 0.828
Muddled 0.486 0.828
Mixed-up 0.614 0.832
Uncertain 0.601 0.828
Extraction method: Principal component analysis. Rotation Method: Varimax, with Kaiser normalization.
Anger and Vigor had factor loadings above 0.63 in all items, without existing cross-loading. In Depression,
the items, depressed”, downhearted”, and unhappyshowed high factor loadings, greater than 0.62. The item
miserableshowed a lower factor loading (0.440). There was cross-loading with the item confused”. For Ten-
sion, the items anxious, worried, and nervousobtained factor loadings higher than 0.72, with no cross-
loading. Fatigue items obtained factor loadings above 0.70 except for sleepy”, which showed a lower factor
loading (0.491). Confusion presented three items with factor loadings above 0.60. The item muddledhad a
lower factor loading and introduced cross-loading with the Depression factor.
The internal consistency of the 24 items was high (α = 0.85). Internal consistency was good for all the factors
identified: Anger α = 0.65; Confusion α = 0.63; Depression α = 0.66; Fatigue α = 0.60; Tension α = 0.65, and
Vigor α = 0.81.
The participants, both men and women, showed high levels of Vigor and low levels of Tension, Depression,
Anger, Fatigue and Confusion (Figure 1), and there are significant differences in the variables Anger, Vigor and
Fatigue between men and women.
R. Brandt et al.
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Figure 1. Mood states of men and women engaged in physical activity, apparently healthy.
*Significant difference at p < 0.05. **Significant difference at p < 0.001.
Separating the participants into age groups (Table 4), there is a significant difference between the moods of
the youngest participants (under 18), adults (between 18 and 60 years) and the elderly (over 60 years).
By analyzing the mood depending on self-perceived health status, participants who showed better perception
had lower levels of Depression, Fatigue and Confusion and Vigor, when compared to those with poorer self-
rated health. With the relationship between sleep and moods, all factors are significantly different between those
with a better perception of quality of sleep.
4. Discussion
The aim of this study was to investigate the construct validity and internal consistency of the BRUMS, so as to
recognize it as an instrument for measuring mental health in different populations, which are physically active
and apparently healthy.
The BRUMS has been used in different populations of athletes and non-athletes, young people and adults [12]
[23], with heart disease [24], and with fibromyalgia [13] [14], among others. Its validation for physically active
and apparently healthy populations showed consistent results, with good reliability and construct validity, as
evidenced by the alpha coefficient and factor loadings, found to be higher than other instrument validation stu-
dies [25].
Generally, the factors were properly loaded in their respective domains. The low cross-existence between the
loading factors is a positive element in the present study, given that other validations showed a higher amount of
cross-loading which does not compromise their results [26]. It has been found that there are six factors with ei-
genvalues above one, similar to those found in Rohlfs et al. [11]. A high internal consistency was observed, with
values of 0.85, whereas all areas had values appropriate for its validation.
In the analysis of the results for the BRUMS application, it is evident that there is a difference in the moods of
men and women, already presented in other studies, as well as for the different age groups [7] [12] [14] [27].
Moreover, in the latter, there is a significant difference in all mood factors. When analyzing the results of the
mood states, it is suggested that researchers investigate these characteristic differences in their populations, the-
reby reducing the possibility of error in the data analysis.
In analyzing the results of the self-assessment of health and sleep, it is clear who has a tendency to better
health and sleep, has a mood with greater vigor and less tension, depression, anger, fatigue and confusion. This
would be consistent with the proposed profile by Morgan [8] entitled the icebergprofile (Figure 1), this being
an ideal mental health model. Corroborating this study demonstrates the importance of sleep to mental health, in
the sense of insufficient or poor sleep can cause mental disorders, impairing cognitive function and performance
[28] [29].
From these analyses it is evident that the use of BRUMS beyond the detection of the over-training syndrome
[11], where it has been used in research to delineate the mood profile of different populations, is that it may also
R. Brandt et al.
130
Table 4. Factors of mood about age, self perceived health status and self perception of sleep quality in physically active sub-
jects, apparently healthy.
Tension Depression Anger Vigor Fatigue Confusion
Associated factors
±
±
±
±
±
±
Age group ** ** ** ** ** **
Less than 18 years (n = 271) 4.8 2.9 1.1 1.2 1.4 2.2 10.7 2.8 3.1 2.7 2.4 2.6
Between 18 and 60 (n = 624) 4.4 3.2 1.6 2.6 1.9 2.9 10.9 3.1 3.6 3.4 2.1 2.6
More than 60 years (n = 385) 2.1 2.4 1.2 2.1 0.7 1.7 9.7 2.8 2.5 2.9 1.1 1.9
Health assessment ** ** * *
Excellent (n = 292) 3.7 3.2 0.8 1.7 1.2 2.3 11.6 2.9 2.7 3.1 1.4 2.1
Good (n = 589) 4.1 2.9 1.3 2.2 1.6 2.5 10.6 2.7 3.2 3.1 2.2 2.4
Regular (n = 134) 3.7 3.1 1.9 2.9 1.7 2.8 9.8 3.1 3.5 3.1 2.1 2.6
Poor (n = 11) 5.7 4.5 3.9 3.5 2.3 3.1 8.7 3.8 4.8 3.8 2.6 3.9
Very bad (n = 5) 2.2 1.6 1.2 2.1 0.6 1.3 10.4 2.9 1.4 1.9 1.0 1.7
Sleep quality perception * ** ** ** ** **
Excellent (n = 105) 4.1 3.0 0.8 1.6 1.4 2.0 12.0 3.1 2.6 2.5 1.5 2.0
Good (n = 419) 4.3 2.9 1.2 2.1 1.5 2.4 11.1 2.7 3.1 2.9 1.9 2.2
Regular (n = 231) 4.8 3.0 1.4 2.4 1.9 2.7 10.5 3.1 3.9 3.6 2.4 2.7
Poor (n = 44) 5.5 3.9 2.7 3.8 3.7 4.2 10.4 2.9 5.3 3.6 3.4 3.4
Very bad (n = 5) 6.2 5.7 7.2 3.9 5.8 4.8 8.0 2.2 6.4 3.7 6.8 4.9
*Significant difference at p < 0.05. **Significant difference at p < 0.001.
be used as a mental health indicator.
5. Conclusion
From the above, considering that researchers are in different contexts and with different populations, their use of
the BRUMS can investigate mental health in different populations, which are physically active and apparently
healthy.
AuthorsContributions
All authors participated in the acquisition of data and revision of the manuscript. All authors determined the de-
sign, interpreted the data and drafted the manuscript. All authors read and gave final approval for the version
submitted for publication.
Declaration of Interest
The authors report no conflict of interest. All authors were responsible for the content and writing of this paper.
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... The BRUMS scale is a subclinical psychological questionnaire correlated with mood states and mental health. 25 BRUMS is used in different contexts, in general physically active populations [25][26][27] and military personnel, 27 including application during expeditions in extreme environments. 10,28 The BRUMS has six dimensions: (1) "Anger," designating a state of hostility, represented by the words Annoyed, Bitter, Angry, or Bad-tempered; (2) "Confusion," represented by the words Confused, Muddled, Mixed-up, Uncertain; (3) "Depression," an emotional state of discouragement, sadness, and unhappiness, represented by the words Depressed, Downhearted, Unhappy, Miserable; (4) "Fatigue," a state of tiredness and low energy, represented by the words Worn out, Exhausted, Sleepy or Tired; (5) "Tension," a musculoskeletal tension and worries, represented by the words Panicky, Anxious, Worried, or Nervous; (6) "Vigor," designating a state of energy and physical strength represented by the words Lively, Energetic, Active, or Alert. ...
... The BRUMS scale is a subclinical psychological questionnaire correlated with mood states and mental health. 25 BRUMS is used in different contexts, in general physically active populations [25][26][27] and military personnel, 27 including application during expeditions in extreme environments. 10,28 The BRUMS has six dimensions: (1) "Anger," designating a state of hostility, represented by the words Annoyed, Bitter, Angry, or Bad-tempered; (2) "Confusion," represented by the words Confused, Muddled, Mixed-up, Uncertain; (3) "Depression," an emotional state of discouragement, sadness, and unhappiness, represented by the words Depressed, Downhearted, Unhappy, Miserable; (4) "Fatigue," a state of tiredness and low energy, represented by the words Worn out, Exhausted, Sleepy or Tired; (5) "Tension," a musculoskeletal tension and worries, represented by the words Panicky, Anxious, Worried, or Nervous; (6) "Vigor," designating a state of energy and physical strength represented by the words Lively, Energetic, Active, or Alert. ...
... 10,28 The BRUMS has six dimensions: (1) "Anger," designating a state of hostility, represented by the words Annoyed, Bitter, Angry, or Bad-tempered; (2) "Confusion," represented by the words Confused, Muddled, Mixed-up, Uncertain; (3) "Depression," an emotional state of discouragement, sadness, and unhappiness, represented by the words Depressed, Downhearted, Unhappy, Miserable; (4) "Fatigue," a state of tiredness and low energy, represented by the words Worn out, Exhausted, Sleepy or Tired; (5) "Tension," a musculoskeletal tension and worries, represented by the words Panicky, Anxious, Worried, or Nervous; (6) "Vigor," designating a state of energy and physical strength represented by the words Lively, Energetic, Active, or Alert. 21,22,25 Each item is preceded by the question "How do you feel right now?" and should be answered on a Likert-type 5-point scale (from 0 = "not at all" to 4 = "extremely"). Therefore, the total score for each dimension ranges from 0 to 16. ...
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In Antarctica, human access and presence are complex and require detailed planning and preparation in advance. The personnel of National Antarctic Programs (NAPs, i.e., scientists and support personnel, including military, civilians, and mountaineers) stay in different isolation, confinement, and extreme (ICE) environments such as ships, research stations, and scientific summer camps. Antarctica imposes harsh conditions that influence physiological and psychological responses impacting health, mood, and physical and cognitive performances. In this context, we argue why people should prepare in advance for staying in Antarctica and what to expect in ICE environments. We also spotlighted recommendations shared by different NAPs participant guides, including predeployment training. Next, we present a case study of the Brazilian Pre-Antarctic Training (PAT), a theoretical-practical training that provides technical and logistical information and assesses the adaptability and physical capacity of researchers and military personnel to perform fundamental activities in a polar environment. We evaluated and compared the individual's mood at the beginning and the end of the PAT week and observed group-specific mood changes depending on the sex, functions, and the facilities that participants accessed. Finally, we proposed that conducting training before staying in Antarctica, besides promoting conditions to better plan the voyage and knowledge of the region, can contribute to dealing with the possible mood swings during expeditions and even promote positive affect. Therefore, the psychophysiological effects of PAT are topics for further investigations.
... Among the different options, stationary cycling can be a safe and valid strategy to promote physical fitness and stay active at home. To remain active while in a social distancing condition is essential since many scientific studies point out that chronic physical exercise benefits both physical conditioning [2] and also cognitive functions [3], helping to protect mental health [4]. To achieve these goals, the exercise requires specific frequency, volume, and intensity [5,6]. ...
... Each participant visited the laboratory three times, with at least 48 hours between visits. Before the physical tests, participants answered questionnaires of anamnesis, the Pittsburgh Sleep Quality Index [19], and the Brunel Mood Scale [4]. Participants would be excluded if they reported sleep difficulties in the previous night or involvement with physical exercise 24 h before the tests (no participant was excluded). ...
... High levels of stress can impair cognitive performance [4,29]. The lack of strong correlations between the results of the cognitive tests with the sleep quality index of the previous month described by the participants indicates that the quality of sleep (good or bad) seems not to have influenced our results. ...
Article
Physical and cognitive exercises have positive long-term effects on cognitive capacities. However, acute effects still are controversial. Here we determine the acute effects of physical exercise combined with concurrent cognitive exercise on cognitive performance in young adults. Simple reaction time, selective attention, and memory were evaluated in 23 young men before and after 30 min of stationary cycling exercise, 30 min of stationary cycling exercise combined with cognitive exercise, and 30 min of rest. Exercise intensity was continuously controlled to ensure exercise at moderate intensity. We found that physical exercise combined with cognitive dual-task improves selective attention. Both exercise conditions showed similar effects on simple reaction time, and memory was not affected by the different exercise conditions. We conclude that the combination of cycling exercise at moderate intensity with a cognitive exercise acutely improves selective attention in young adults. These results can be of particular interest for interventions aiming at improving selective attention in sports and for older adults and individuals with difficulty to suppress and filter out task-irrelevant information, like when receiving instruction or learning a new task or concept.
... However, a 24-item abbreviated POMS called the Brunel Mood Scale (BRUMS) was developed and validated for both adolescents and adults (Terry et al., 1999(Terry et al., , 2003. The BRUMS is being widely used as an assessment tool for evaluating mental health in the general people (Brandt et al., 2016), and clinical patients (Galambos et al., 2005); identifying the suicidal tendency among youth (Gould et al., 2005); assessing the risk of post-traumatic stress disorder among military combats (van Wijk et al., 2013); and assessing mood responses to sports performance (Terry, 1995). ...
... The association of the BRUMS subscales with mental health was in line with earlier studies which supports its concurrent validity. Mental health was negatively associated with anger, confusion, depression, fatigue, and tension while positively correlated with vigor (Brandt et al., 2016;Morgan et al., 1987). This finding was also consistent with the mental health model proposed by Morgan (1980) which states better mental health indicates higher vigor with lower anger, confusion, depression, fatigue, and tension. ...
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Mood assessment is an effective way to monitor mental health states and detect potential psychiatric symptoms. The Brunel Mood Scale (BRUMS) is one of the most widely used self-report measures for assessing mood responses. The current study examined the psychometric properties of the Bangla version of BRUMS and validated it with the Positive Mental Health scale (PMH-scale). The participants were 1015 Bangladeshi university students (62% men) aged from 18 to 27 (M= 21.95, SD= 1.95). The confirmatory factor analysis (CFA) approach was used to test the factor structure of the BRUMS and measurement invariance for sex. The CFA revealed that the originally proposed six-factor model of BRUMS had an acceptable fit which confirms factorial validity. Moreover, each subscale (anger, confusion, depression, fatigue, tension, and vigor) of the BRUMS showed high internal consistency (α ranged from .77 to .87) and retest reliability (ICC ranged from .71 to .91). Concurrent validity of the BRUMS was supported through the hypothesized relationships with mental health (PMH-scale). Full measurement invariance by sex was confirmed for the 6-factor model indicating that the BRUMS is equally applicable to men and women. Finally, normative data were established which allows group comparison of mood scores. This study indicates that the Bangla version of BRUMS can be reliably used to assess mood response which facilitates mood-related research and intervention to improve mental health and reduce psychiatric disorders in Bangladesh.
... The EEG data recording followed several steps. First, the participants were asked to fill out a Brunel Mood Scale questionnaire before starting the recording [32]. Second, participants were asked to perform the task for three minutes to familiarize themselves with the nature of the SCWT. ...
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Vigilance level assessment is of prime importance to avoid life-threatening human error. Critical working environments such as air traffic control, driving, or military surveillance require the operator to be alert the whole time. The electroencephalogram (EEG) is a very common modality that can be used in assessing vigilance. Unfortunately, EEG signals are prone to artifacts due to eye movement, muscle contraction, and electrical noise. Mitigating these artifacts is important for an accurate vigilance level assessment. Independent Component Analysis (ICA) is an effective method and has been extensively used in the suppression of EEG artifacts. However, in vigilance assessment applications, it was found to suffer from leakage of the cerebral activity into artifacts. In this work, we show that the wavelet ICA (wICA) method provides an alternative for artifact reduction, leading to improved vigilance level assessment results. We conducted an experiment in nine human subjects to induce two vigilance states, alert and vigilance decrement, while performing a Stroop Color–Word Test for approximately 45 min. We then compared the performance of the ICA and wICA preprocessing methods using five classifiers. Our classification results showed that in terms of features extraction, the wICA method outperformed the existing ICA method. In the delta, theta, and alpha bands, we obtained a mean classification accuracy of 84.66% using the ICA method, whereas the mean accuracy using the wICA methodwas 96.9%. However, no significant improvement was observed in the beta band. In addition, we compared the topographical map to show the changes in power spectral density across the brain regions for the two vigilance states. The proposed method showed that the frontal and central regions were most sensitive to vigilance decrement. However, in this application, the proposed wICA shows a marginal improvement compared to the Fast-ICA.
... More specifically, it would be anticipated that anyone reporting an inverse Everest profile, characterized by a low Vigor score, high scores for Tension and Fatigue, and very high scores for Depression, Anger, and Confusion, would be a candidate for follow-up assessment by a clinical psychologist or other health professional. Exploring use of the BRUMS-LTU as a mental health screening tool may be a fruitful avenue for future research in Lithuania, considering that the BRUMS has frequently been used for this purpose in English-speaking countries [26][27][28]37]. ...
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Mood can be considered as a diffuse and global emotional state, with both valence and arousal characteristics, that is not directed towards a specific object. Investigation of moods in specific language and cultural contexts relies on the availability of appropriately validated measures. The current study involved the translation and validation of the Brunel Mood Scale (BRUMS) from English into Lithuanian. The 24-item, 6-factor scale, referred to as the BRUMS-LTU, was administered to 746 participants who were fluent in Lithuanian (nmen = 199 (26.7%), nwomen = 547 (73.3%); age range = 17–78 years, M = 41.8 years, SD = 11.4 years). Confirmatory factor analysis showed an adequate fit of the hypothesized measurement model to the data (CFI = 0.954, TLI = 0 .944, RMSEA = 0 .060 [CI 0.056, 0.064], SRMR = 0.070) and multi-sample analysis supported configural, metric, scalar, and residual invariance across genders. Concurrent measures (i.e., Perceived Stress Scale, Big Five Personality Test) correlated with subscale scores in line with theoretical predictions, supporting both convergent and divergent validity. Internal consistency coefficients of the six subscales were satisfactory. Mood scores varied significantly by gender, with men generally reporting more positive moods than women. Findings support the adequacy of the psychometric properties of the BRUMS-LTU. Thus, the scale can be recommended for use in further psychological studies of mood in Lithuania and may also be useful for applied practitioners.
... Staleness is also a recurring behaviour in adolescent athletes, as 30-48% of them reported being stale at least once in a season [20]. The effect of these factors and their correlation with physiological changes are also well studied [19,20] and sometimes incorporated into adult athletes' training, however they are underrepresented among adolescent athletes; however, there are tendentious differences in their mood states [21]. ...
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Background: Continuously rising performances in elite adolescent athletes requires increasing training loads. This training overload without professional monitoring, could lead to overtraining in these adolescents. Methods: 31 elite adolescent athletes (boys: n = 19, 16 yrs; girls: n = 12, 15 yrs) participated in a field-test which contained a unified warm-up and a 200 m maximal freestyle swimming test. Saliva samples for testosterone (T) in boys, estradiol (E) in girls and cortisol (C) in both genders were collected pre-, post- and 30 min post-exercise. Lactate levels were obtained pre- and post-exercise. Brunel Mood Scale, Perceived Stress Scale and psychosomatic symptoms questionnaires were filled out post-exercise. Results: Lactate levels differed between genders (boys: pre: 1.01 ± 0.26; post: 8.19 ± 3.24; girls: pre: 0.74 ± 0.23; post: 5.83 ± 2.48 mmol/L). C levels increased significantly in boys: pre- vs. post- (p = 0.009), pre- vs. 30 min post-exercise (p = 0.003). The T level (p = 0.0164) and T/C ratio (p = 0.0004) decreased after field test which draws attention to the possibility of overtraining. Maximal and resting heart rates did not differ between genders; however, heart rate recovery did (boys: 29.22 ± 7.4; girls: 40.58 ± 14.50 beats/min; p = 0.008). Conclusions: Our models can be used to explain the hormonal ratio changes (37.5-89.8%). Based on the results this method can induce hormonal response in elite adolescent athletes and can be used to notice irregularities with repeated measurements.
... The humor status was assessed before each of the exercise sessions using the Brunel Mood Scale, BRUMS. 15,16 On the second and third visits, participants performed submaximal cycling trials on the same cycle ergometer at the workload of 50% of their maximal power output. The two submaximal sessions were performed until voluntary exhaustion or a time limit of 60 minutes. ...
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BACKGROUND: Dissociation by music may impact the rate of perceived exertion (RPE), which is an indicator of internal loads during exercise. However, it is not clear how music affects the RPE, neuromuscular, and cognitive responses to exercise. AIM: To determine whether listening to preferred music during indoor endurance exercise influences RPE, neuromuscular, and cognitive responses in healthy individuals. METHOD: Thirteen healthy adults performed sessions of prolonged indoor cycling at moderate intensity while listening or not to preferred music. Reaction time, selective attention, and memory were evaluated before, during, and/or after the exercise sessions. RPE, heart rate, muscle activation, pedaling torque, and cadence were recorded during the exercises. RESULTS: RPE (P = 0.004, d = 0.40), heart rate (P = 0.048, d = 0.53) and cadence (P = 0,043; d = 0.51) were higher in the music session compared to no music. Selective attention (P = 0.233), simple reaction time (P = 0.360), working and short-term memory (P > 0.05), as well as torque (P = 0.262) and muscle activation (RMS and MDF, P > 0.05) did not differ between music and no music sessions. CONCLUSION: Indoor cycling while listening to preferred music elicited higher internal loads, which we consider a result of higher cardiovascular demand. However, the effects of music on neuromuscular and cognitive responses were not evident. We conclude that music can be helpful to improve demand during indoor exercise.
... Mood was assessed using the Brunel Mood Scale (BRUMS) [32,33] which has been validated for use in healthy adult populations [34]. BRUMS is a 24-item questionnaire of simple mood descriptors divided across six subscales: anger, confusion, depression, fatigue, tension, and vigour. ...
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Background Office work generally consists of high amounts of sedentary behaviour (SB) which has been associated with negative health consequences. We developed the “WorktivIty” mobile app to help office workers reduce their SB through self-monitoring and feedback on sedentary time, prompts to break sedentary time, and educational facts. The aim of this paper is to report the feasibility of delivering the Worktivity intervention to desk-based office workers in the workplace setting and describe methodological considerations for a future trial. Methods We conducted a three-arm feasibility cluster randomised controlled pilot study over an 8-week period with full time-desk based employees. Clustered randomisation was to one of three groups: Worktivity mobile app (MA; n = 20), Worktivity mobile app plus SSWD (MA+SSWD; n = 20), or Control (C; n = 16). Feasibility was assessed using measures of recruitment and retention, intervention engagement, intervention delivery, completion rates and usable data, adverse events, and acceptability. Results Recruitment of companies to participate in this study was challenging (8% of those contacted), but retention of individual participants within the recruited groups was high (81% C, 90% MA + SSWD, 95% MA). Office workers’ engagement with the app was moderate (on average 59%). Intervention delivery was partially compromised due to diminishing user engagement and technical issues related to educational fact delivery. Sufficient amounts of useable data were collected, however either missing or unusable data were observed with activPAL™, with data loss increasing at each follow up time point. No serious adverse events were identified during the study. The majority of participants agreed that the intervention could be implemented within the workplace setting (65% MA; 72% MA + SSWD) but overall satisfaction with the intervention was modest (58% MA; 39% MA + SSWD). Conclusions The findings suggest that, in principle, it is feasible to implement a mobile app-based intervention in the workplace setting however the Worktivity intervention requires further technical refinements before moving to effectiveness trials. Challenges relating to the initial recruitment of workplaces and maintaining user engagement with the mHealth intervention over time need to be addressed prior to future large-scale implementation. Further research is needed to identify how best to overcome these challenges.
... Scan this QR code with your smart phone or mobile device to read online. characterised by above average scores for tension, depression, anger, fatigue and confusion and below average scores for vigour, has been associated with poorer general mental health, 20 and an increased risk for a range of specific psychopathologies, including chronic fatigue, post-traumatic stress disorder and eating disorders. 21,22,23 Recent research on mood state responses during COVID-19 reported an inverse iceberg profile in an international sample. ...
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The effect of coronavirus disease 2019 (COVID-19) on the mood responses of individuals is an important indicator of how society is coping with the pandemic. Characterising mood responses in a South African sample could prepare clinicians for possible presentations of mental health concerns in general practice. This study described mood responses during COVID-19 Alert Level 1. The sample of 641 participants who completed the Brunel Mood State Scale during November 2020 was drawn from primary healthcare and family medicine clinics and practices in Cape Town. Their mood response profile was described and compared with pre-COVID-19 norms. The mood profile represented an inverse iceberg profile, with mean scores deviating significantly from pre-COVID-19 norms across all six mood dimensions measured. The inverse iceberg profile had been associated with a range of psychopathologies, suggesting an increased risk of psychological disorders. The current profile of mood responses could alert clinicians to the possibility of increased mental health needs of patients. Patient reports of prolonged anxiety and fatigue, particularly when combined with low mood and low vigour, could signal the need for intervention or referral for further mental health support.
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Sleep and mood states are psychological aspects influenced by the practice of physical exercise, thus, the objective of the research was to investigate the effect of 16 weeks of running in relation to thesleep self-assessmentand changes in the states of humor. Eighteen recreational runners (13 Women; 5 Men) participated in the research. The Brunel Mood Scale (BRUMS) assessed Mood States, being transported before and after training, while the self-reported question about sleep was done just before training. Descriptive and inferential statistics were applied to assess the relationships between sleep, mood and running, differences were considered statistically significantly when p < 0.05. The results showed 5 dissipate from the mood variables anger, tension, distortion, confusion and fatigue, dissipate changes before and after the intervention, while vigor did not change. The effect size showed a large magnitude in reduction of anger and depression, moderate reduction in tension and confusion, negligible reduction in vigor, and a small increase in magnitude of fatigue. Regarding sleep self-assessment, there was no difference before and after the intervention. It can be observed that a moderate intensity street running practice can improve sleep quality and maintain adequate levels of mood. Keywords:Exercise; Race; Humor; Sleep
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JUSTIFICATIVA E OBJETIVOS: A síndrome da fibromialgia (SFM) é de difícil diagnóstico e tratamento, caracterizada pela ocorrência de dores musculoesqueléticas associadas a distúrbios do sono, rigidez matinal, cefaleia crônica e distúrbios psíquicos. O objetivo deste estudo foi avaliar os efeitos de 32 sessões de caminhada orientada sobre a qualidade do sono, estados de humor, depressão e impacto da SFM sobre a qualidade de vida de mulheres com SFM. MÉTODO: Foram incluídas nove mulheres com diagnóstico clínico de SFM, com média de idade de 48 ± 10 anos. A qualidade do sono foi avaliada por meio do Índice de Qualidade do Sono de Pittsburgh (PSQI), os estados de humor pela Escala de Humor de Brunel (BRUMS), a depressão pelo Inventário de Depressão de Beck (BDI) e o impacto da SFM sobre a qualidade de vida pelo Questionário de Impacto da SFM (FIQ). As participantes foram avaliadas antes e após a prática de 32 sessões de caminhada orientada. Os dados foram analisados utilizando-se o teste t Pareado com α de 0,05 (p < 0,05). RESULTADOS: Após as 32 sessões de caminhada orientada as participantes apresentaram melhora significativa na qualidade do sono e nos estados de humor, em especial nas variáveis tensão, depressão, raiva e confusão mental. Não foram observadas diferenças significativas na depressão e no impacto da SFM sobre a qualidade de vida. CONCLUSÃO: A prática de caminhada melhorou de forma significativa a qualidade do sono e os estados de humor de mulheres com SFM.
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p> Objective: The Brunel Mood Scale (BRUMS) has proved useful to assess mood states in a range of clinical settings. Its local utility is restricted by the lack of normative data from South Africa. This paper presents preliminary normative data for the use of the BRUMS in the South African health care setting. Method: Participants (N=2200), ranging from 18 to 59 years, employed in the public sector, and were recruited during routine occupational health surveillance, completed the 24-item self-report BRUMS. They came from all South African race and language groups, and from all nine provinces. Results: Significant differences were found between the scores of women and men, and their results are reported separately. Due to the language dependant nature of the BRUMS, results are also reported separately for respondents with English as first language, and those who have other South African languages as mother tongue. Norm tables with T-scores are presented for the full sample, and per gender X language groups. Conclusion: This study presents normative data for a sample of educated and employed South Africans from various backgrounds. Its brevity, and provisionally language friendly nature makes it a useful measure for screening psychological distress in the SA clinical health care context.</p
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A number of studies seem to confirm a degradation of mental health among students in higher education. By developing a “mental health profile” for these students, the aim is to adequately specify remedial actions and initiatives. A sample of 1031 college students was used. The results found were: the mental health is superior to the general population, but the depressive symptomatology is superior to the normal population; probably 32.1% of young adults are emotionally disturbed; marijuana is the drug preferred by students, followed by tranquilizers and barbiturates and the majority of this population do not engage in physical exercise. The conclusions of this study can be used to develop a number of recommendations to be discussed with education counseling bodies.
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Background Research development is needed in physical activity and sedentary behaviour and their associations with mental health in young people. In Western countries the weather is a key contributing factor of sedentary behaviour in youth. The likely contributing factor of sedentary behaviour among African youth has not been explored. This study examined the association between sedentary behaviour and mental health in African young people. Methods Participants were 296 adolescents (150 males, 146 females) aged 13 to 18 years (mean = 14.85 years) living in Ghana. Participants’ physical activity levels were assessed using the Physical Activity Questionnaire for Older Adolescents (PAQ-A) and sedentary behaviour, using the Adolescents Sedentary Activity Questionnaire. Depression was assessed using the Children Depression Inventory and aspects of self-esteem were measured with the Physical Self-worth test and Body Image Silhouette test. Results There was a significant negative correlation between physical activity and mental health independent of sedentary behaviour [depression (r =-0.78, p < 0.001); physical self-worth (r = 0.71, p < 0.001); body dissatisfaction (r =-0.76, p < 0.001)]. Moreover, sedentary behaviour was significantly associated with higher depression (r = 0.68, p < 0.001). Affluence was a significant contributing factor of sedentary behaviour in African young people [t (294) =-7.30, p < 0.001]. Conclusion The present study has found that sedentary behaviour is highly prevalent among African adolescents especially among adolescents from affluent homes. Low levels of physical activity as well as sedentary behaviour is significantly associated with mental health problems among African youth, which is consistent with reports from studies among Western young people. The present research, therefore, contributes new information to the existing literature. Increased physical activities can improve the mental health of adolescents.
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The purpose of this research was to investigate the gender differences of the influential factors on the mental health condition among university teachers in the A university in Japan. A questionnaire survey was mailed to 924 university teachers in Japan, with a survey return rate of 43.8% (N=405). The General Health Questionnaire 28 (GHQ-28), Multidimensional Scale of Perceived Social Support (MSPSS), the Japanese version of the Brief Coping Orientation to Problems Experienced (COPE) and the Work Situation Questionnaire (WSQ) developed by the authors were administered to subjects. The GHQ-28 total score and all of sub-score of the woman was significantly higher than men. In the correlated factor of mental health, level of job satisfaction and job control, social support of significant others was observed in the both sexes. However, gender differences was observed in the coping style. Some copings including self-distraction and self-blame were related to the men, but the woman was related to the substance use. University teachers had some gender differences in the factors affecting their mental health condition. In order to improve university teacher's mental health condition, it is necessary to increase their level of job satisfaction and feeling of job control in the workplace. Especially, it was considered women's coping using substance use was important. J. Med. Invest. 62: 56-61, February, 2015.
Article
This study aimed to investigate the effects of sleep deprivation on serum cortisol level and mental health and explore the correlations between them in servicemen. A total of 149 out of the 207 Chinese servicemen were randomly selected to go through 24 hours sleep deprivation, leaving the rest (58) as the control group, before and after which their blood samples were drawn for cortisol measurement. Following the procedure, all the participants were administered the Military Personnel Mental Disorder Prediction Scale, taking the military norm as baseline. The results revealed that the post-deprivation serum cortisol level was positively correlated with the factor score of mania in the sleep deprivation group (rSp=0.415, p<0.001). Sleep deprivation could significantly increase serum cortisol level and may affect mental health in servicemen. The increase of serum cortisol level is significantly related to mania disorder during sleep deprivation. Copyright © 2015. Published by Elsevier B.V.
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Mood states of youth have a strong influence on their cooperation, comfort, and engagement in many health care and educational settings. Children who are fearful, angry, or sad are more likely to have difficulty learning new skills or connecting with others. Many interventions are used in hospital and school settings to help youth, but it is difficult to assess their effectiveness without appropriate assessment tools that are easy to administer, age appropriate, and psychometrically sound. We examined the validity and reliability of the Fast Assessment of Children's Emotions (FACE). After obtaining parental consent and youth assent, 61 patients ages 12 to 17 years were recruited from the psychiatry services at a large children's hospital. Participants completed the FACE, the Brunel Mood Scale (BRUMS), and a measure of satiety at three time points-before and after a 60-minute psychotherapeutic intervention and after lunch. The FACE measure was significantly correlated with the BRUMS (r(2) = 0.85; p < .001) and not correlated with the satiety measure (r(2) = -0.17; not significant). Cronbach's α for the FACE was 0.7734. The FACE showed significant changes in mood from before to after the therapeutic intervention for all patients. For general psychiatry patients, the FACE did not change significantly after lunch, although for patients with eating disorders, the FACE did indicate an increase in distressed emotions after lunch. This finding indicates sensitivity to change in a clinically meaningful manner. The FACE is easy to use and may be used quickly to assess mood changes in adolescents. Copyright © 2015 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.